From 56281a0ec075313ffcf89bafbac9cd65f403c994 Mon Sep 17 00:00:00 2001
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Date: Thu, 30 Apr 2026 11:13:17 +0000
Subject: [PATCH] =?UTF-8?q?feat(GSIFI-AIMS-BLUEPRINT-WP-037)=20v1.0.0=20?=
 =?UTF-8?q?=E2=80=94=20Regulator-Grade=20AI=20Governance=20&=20ISO/IEC=204?=
 =?UTF-8?q?2001=20AIMS=20Master=20Blueprint=20for=20G-SIFIs=20(2026-2030)?=
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- 12 modules / 44 sections / 8 schemas / 11 code examples / 5 case studies / 78 API routes
- AIMS documentation Sections 1-5 (ISO/IEC 42001 Cl. 4-10) + Annexes J1-J4
- Multi-jurisdiction overlays: ECB SSM, Fed SR 11-7, PRA SS1/23, EU AI Act, GDPR
- Regulator Submission Packs RSP v1.0 -> v2.6 with decision-traceability API,
  in-toto/Cosign/Rekor signing, PQC-ready (Dilithium hybrid), ZK predicates
- Terraform + OPA technical enforcement: 5 modules, 7 policy bundles,
  5 decision points (TF plan, CI gate, admission ctrl, runtime, egress)
- Adversarial governance loop + 4 self-healing playbooks (SH-01..04)
- Predictive governance (Prophet/ARIMA forecasters) + formally-verified
  obligation graph (TLA+/Lean for FCRA §615, GDPR Art. 22, EU AI Act Art. 73,
  ECB ICAAP) + counterfactual/causal supervisor queries
- Cross-regulator FedReg federation (mTLS + SPIFFE) + Autonomous Supervisory
  Tiers T0..T5 + joint ECB+Fed+PRA examination workflow
- High-risk credit underwriting reference pattern (AI-CR-UNDERWRITE-01,
  EU AI Act Annex III §5(b))
- 5-phase 2026-2030 roadmap (Foundation -> Industrialise -> Federate ->
  Verify -> Autonomous), 16 board-tracked KPIs, 3LoD + RACI + 5 committees
- Reporting templates with <title>/<abstract>/<content> tags
- Schemas: AI System Inventory, RSP Manifest, Decision Envelope, Control
  Mapping, FRIA, Incident Record, FedReg Message, Obligation Spec
- 11 code examples: OPA RSP gate, Terraform WORM evidence (10y), decision
  envelope dual-signer (Ed25519+Dilithium3), fairness monitor + SH-01,
  FedReg client, drift forecaster, TLA+ Art.73 spec, Lean FCRA spec,
  self-healing engine, FastAPI traceability API, Merkle anchor
- Generators: gen-gsifi-aims-blueprint.py (63 KB JSON) +
  gen-gsifi-aims-blueprint-html.py (76 KB HTML)
- Server.js: /api/gsifi-aims/* endpoint family wired with /:id route ordering
  (specific paths declared before parametric to avoid shadowing)
- Validated: node -c OK; PM2 online; HTTP 200 across modules M1-M12,
  endpoint groups (overlays, RSP versions, AIMS sections/annexes, roadmap
  phases/KPIs, RACI, schemas/code/cases); 8 lookup tests passed; 7 404
  handling cases verified; HTML dashboard 78,241 bytes
---
 .../data/gsifi-aims-blueprint.json            | 1612 ++++++++++++++++
 .../gen-gsifi-aims-blueprint-html.py          |  406 ++++
 .../gen-gsifi-aims-blueprint.py               | 1716 +++++++++++++++++
 .../public/gsifi-aims-blueprint.html          |  774 ++++++++
 rag-agentic-dashboard/server.js               |  230 +++
 5 files changed, 4738 insertions(+)
 create mode 100644 rag-agentic-dashboard/data/gsifi-aims-blueprint.json
 create mode 100644 rag-agentic-dashboard/gen-gsifi-aims-blueprint-html.py
 create mode 100644 rag-agentic-dashboard/gen-gsifi-aims-blueprint.py
 create mode 100644 rag-agentic-dashboard/public/gsifi-aims-blueprint.html

diff --git a/rag-agentic-dashboard/data/gsifi-aims-blueprint.json b/rag-agentic-dashboard/data/gsifi-aims-blueprint.json
new file mode 100644
index 0000000..a3af74b
--- /dev/null
+++ b/rag-agentic-dashboard/data/gsifi-aims-blueprint.json
@@ -0,0 +1,1612 @@
+{
+  "meta": {
+    "docRef": "GSIFI-AIMS-BLUEPRINT-WP-037",
+    "version": "1.0.0",
+    "date": "2026-04-30",
+    "title": "Regulator-Grade AI Governance & ISO/IEC 42001 AIMS Master Blueprint for G-SIFIs (2026-2030)",
+    "subtitle": "Design and implementation roadmap for ISO/IEC 42001-aligned AI Management Systems, multi-jurisdiction regulatory overlays, Regulator Submission Packs (RSP v1.0-v2.6), Terraform/OPA technical enforcement, adversarial and self-healing governance loops, predictive governance with formally-verified legal logic, cross-regulator federation, and autonomous supervisory ecosystems for high-risk credit underwriting.",
+    "classification": "CONFIDENTIAL \u2014 Board / Prudential Regulator / Group Risk / Internal Audit / Chief Legal & Compliance Officer",
+    "owner": "Group CRO + Chief AI Officer (CAIO) \u2014 co-signed by CCO, GC, CISO, DPO, Head of Internal Audit",
+    "audience": [
+      "Board of Directors / Risk Committee / Audit Committee",
+      "Executive Committee (CEO, CFO, CRO, CCO, CISO, CAIO, CTO)",
+      "Group Compliance, Legal & Privacy Office",
+      "Internal Audit (3rd Line of Defense)",
+      "Model Risk Management (MRM, 2nd Line of Defense)",
+      "Prudential supervisors (ECB SSM JST, Federal Reserve, PRA, OCC)",
+      "Conduct supervisors (FCA, BaFin, AMF, CFPB)",
+      "Data protection authorities (EDPB, ICO)",
+      "AI safety / standards bodies (AISI, ISO/IEC JTC1 SC42)"
+    ],
+    "horizon": "2026-2030",
+    "outlookHorizon": "2030-2035 (autonomous supervisory ecosystems)",
+    "subjectSystem": {
+      "institutionType": "G-SIFI / G-SIB (FSB list, Bucket 1-4)",
+      "scopeOfAi": "All AI systems materially impacting capital, liquidity, credit, market conduct, AML, fraud, and customer outcomes",
+      "anchorUseCase": "AI-CR-UNDERWRITE-01 \u2014 High-risk retail & SME credit underwriting (EU AI Act Annex III \u00a75(b) \u2014 high-risk)",
+      "scale": "20+ jurisdictions \u00b7 1,200+ AI systems \u00b7 350+ models in production"
+    },
+    "regulatoryAlignment": [
+      "ISO/IEC 42001:2023 \u2014 AI Management System (AIMS) \u2014 primary anchor",
+      "ISO/IEC 23894:2023 \u2014 AI Risk Management",
+      "ISO/IEC 5338:2023 \u2014 AI System Life Cycle Processes",
+      "ISO/IEC 27001:2022 / 27701:2019 / 27018:2019",
+      "ISO/IEC TR 24028 / 24029 / 24368 (trustworthiness)",
+      "EU AI Act (Reg. (EU) 2024/1689) \u2014 Art. 6, 9, 10, 12, 13, 14, 15, 17, 26, 27, 49, 53, 55, 72, 73; Annex III \u00a75(b)",
+      "GDPR (Reg. (EU) 2016/679) \u2014 Art. 5, 6, 9, 22, 25, 32, 33, 34, 35",
+      "ECB SSM Guide on internal models (2024) + Targeted Review of Internal Models (TRIM) AI extensions",
+      "Federal Reserve SR 11-7 / OCC 2011-12 \u2014 Model Risk Management",
+      "PRA SS1/23 \u2014 Model Risk Management Principles for Banks (UK)",
+      "PRA SS2/21 \u2014 Outsourcing & third-party risk management",
+      "FCA Consumer Duty (PS22/9) + AI/ML discussion paper DP5/22",
+      "Basel III/IV \u2014 CRR3 / CRD6 \u2014 ICAAP Pillar 2 AI add-on",
+      "FCRA (US) \u00a7604/\u00a7615 + ECOA / Reg B \u00a71002 (adverse action)",
+      "CFPB Circular 2023-03 (algorithmic adverse-action notices)",
+      "NIST AI RMF 1.0 + GenAI Profile (AI 600-1)",
+      "OECD AI Principles + G7 Hiroshima AI Process Code of Conduct",
+      "Council of Europe Framework Convention on AI (2024)",
+      "OWASP LLM Top 10 (2025) / MITRE ATLAS",
+      "SLSA L3 + Sigstore/Cosign + in-toto attestations"
+    ],
+    "deliverableInventory": {
+      "modules": 12,
+      "aimsSections": 5,
+      "annexes": 4,
+      "regulatoryOverlays": 5,
+      "rspVersions": 7,
+      "schemas": 8,
+      "codeExamples": 11,
+      "caseStudies": 5,
+      "phases": 5,
+      "kpis": 16,
+      "controls": 280
+    }
+  },
+  "executiveSummary": {
+    "purpose": "Provide G-SIFI boards, regulators, and supervisors a regulator-grade, ISO/IEC 42001-anchored master blueprint that operationalises AI governance across all jurisdictions in which the institution operates, with machine-checkable legal logic and autonomous supervisory federation by 2030.",
+    "scope": "End-to-end design, implementation, and continuous-supervision framework for an AI Management System (AIMS) covering all material AI systems \u2014 anchored on the AI-CR-UNDERWRITE-01 high-risk credit use case.",
+    "designPrinciples": [
+      "ISO/IEC 42001 as the operating standard, regulator overlays as policy bundles",
+      "Compliance-as-code: every control has Terraform + OPA enforcement",
+      "Decision-traceability: every model decision is reproducible from a signed envelope",
+      "Self-healing governance: detect-then-remediate loops with cryptographic evidence",
+      "Predictive governance: forecast control breaches before they occur",
+      "Formally-verified legal logic: TLA+/Lean specs of obligations",
+      "Federation by default: cross-regulator API with consented disclosure",
+      "Adversarial assurance: continuous red-teaming of both models and controls"
+    ],
+    "headlineKpis": {
+      "timeToRegulatorApprovedDeployment": "<= 14 days (RSP v2.4+)",
+      "rspGenerationLatency": "<= 30 minutes (auto-assembled, signed)",
+      "decisionTraceabilityCoverage": ">= 99.95% of AI decisions",
+      "controlAutomationRate": ">= 95% (Terraform + OPA enforced)",
+      "evidenceAutomation": ">= 96% (no human evidence collection for L1/L2 controls)",
+      "fairnessAirFloor": ">= 0.85 (FCRA / ECOA / EU AI Act Art. 10)",
+      "explainabilityCoverage": "100% of high-risk decisions have SHAP + counterfactual",
+      "adverseActionNoticeSla": "<= 30 days (FCRA \u00a7615) \u2014 automated for 100% cases",
+      "incidentNotifSlaRegulator": "<= 24h (EU AI Act Art. 73) / 72h (GDPR Art. 33)",
+      "modelInventoryCoverage": "100% \u2014 no shadow AI tolerance",
+      "policyDriftMtta": "<= 5 minutes (Terraform plan diff)",
+      "autonomousSupervisorReadiness": "Tier-3 by 2030 (machine-readable filings)",
+      "boardAttestationCadence": "Quarterly + ad-hoc on Sev-1",
+      "auditFindingCloseRate": ">= 95% within SLA",
+      "wormRetention": "10 years (extends SR 11-7 / SEC 17a-4(f) baseline)",
+      "crossRegulatorFederationCount": ">= 8 supervisors integrated"
+    },
+    "boardNarrative": "This blueprint converts AI governance from a periodic compliance exercise into a continuously-attested, regulator-federated operating discipline \u2014 measurable, monitorable, and provably correct against the EU AI Act, ISO/IEC 42001, ECB, Fed, PRA, and GDPR by design."
+  },
+  "M1_aimsSections": {
+    "id": "M1",
+    "title": "M1 \u2014 ISO/IEC 42001 AIMS Documentation (Sections 1\u20135)",
+    "summary": "Master AIMS documentation set anchored on ISO/IEC 42001:2023 clauses 4\u201310, broken into Sections 1\u20135 with audit-grade detail.",
+    "sections": [
+      {
+        "id": "M1-S1",
+        "title": "Section 1 \u2014 Context of the Organization (Cl. 4)",
+        "iso42001Clauses": [
+          "4.1",
+          "4.2",
+          "4.3",
+          "4.4"
+        ],
+        "deliverables": [
+          "Internal/external issues register (PEST + tech + regulatory)",
+          "Interested parties matrix (regulators, customers, employees, society)",
+          "AIMS scope statement (geographies, business units, AI systems)",
+          "AI System Inventory v1 (1,200+ systems, classification)",
+          "Boundary diagram showing AIMS interfaces with EMS/ISMS/QMS"
+        ],
+        "evidenceRefs": [
+          "EVD-AIMS-S1-CTX-2026Q2",
+          "EVD-AIMS-S1-INV-2026Q2"
+        ]
+      },
+      {
+        "id": "M1-S2",
+        "title": "Section 2 \u2014 Leadership & Policy (Cl. 5)",
+        "iso42001Clauses": [
+          "5.1",
+          "5.2",
+          "5.3"
+        ],
+        "deliverables": [
+          "Board-approved AI Policy (signed by Chair + CEO)",
+          "AI Roles & Responsibilities matrix (RACI: Board, CAIO, CRO, CCO, DPO)",
+          "Authority delegation: model approval thresholds by Tier T0\u2013T5",
+          "Conflict-of-interest controls between 1st/2nd/3rd LoD"
+        ],
+        "evidenceRefs": [
+          "EVD-AIMS-S2-POL-2026Q2",
+          "EVD-AIMS-S2-RACI-2026Q2"
+        ]
+      },
+      {
+        "id": "M1-S3",
+        "title": "Section 3 \u2014 Planning (Cl. 6)",
+        "iso42001Clauses": [
+          "6.1",
+          "6.2",
+          "6.3"
+        ],
+        "deliverables": [
+          "AI Risks & Opportunities register (linked to ISO 23894 taxonomy)",
+          "AI Objectives (16 KPIs, board-tracked)",
+          "Change planning protocol (model promotion gates G0\u2013G5)",
+          "Statement of Applicability (SoA) covering Annex A + regulator overlays"
+        ],
+        "evidenceRefs": [
+          "EVD-AIMS-S3-RISK-2026Q2",
+          "EVD-AIMS-S3-SOA-2026Q2"
+        ]
+      },
+      {
+        "id": "M1-S4",
+        "title": "Section 4 \u2014 Support (Cl. 7)",
+        "iso42001Clauses": [
+          "7.1",
+          "7.2",
+          "7.3",
+          "7.4",
+          "7.5"
+        ],
+        "deliverables": [
+          "Resourcing plan (FTEs, GPU compute, evidence storage)",
+          "Competence framework (CAIO certification, MRM accreditation)",
+          "Awareness program (annual mandatory training, red-team exercises)",
+          "Communication plan (internal + regulator + customer)",
+          "Documented information control (versioning, WORM, retention)"
+        ],
+        "evidenceRefs": [
+          "EVD-AIMS-S4-COMP-2026Q2",
+          "EVD-AIMS-S4-DOC-2026Q2"
+        ]
+      },
+      {
+        "id": "M1-S5",
+        "title": "Section 5 \u2014 Operation, Performance, Improvement (Cl. 8\u201310)",
+        "iso42001Clauses": [
+          "8.1",
+          "8.2",
+          "8.3",
+          "9.1",
+          "9.2",
+          "9.3",
+          "10.1",
+          "10.2"
+        ],
+        "deliverables": [
+          "Operational planning & control (life-cycle SOPs per ISO 5338)",
+          "AI impact assessment process (GDPR DPIA + EU AI Act FRIA)",
+          "Performance evaluation (KPI dashboard, internal audit plan)",
+          "Management review minutes (quarterly, board-attested)",
+          "Continual improvement loop (CAPA register, RCA)"
+        ],
+        "evidenceRefs": [
+          "EVD-AIMS-S5-OPS-2026Q2",
+          "EVD-AIMS-S5-MR-2026Q2",
+          "EVD-AIMS-S5-CAPA-2026Q2"
+        ]
+      }
+    ]
+  },
+  "M2_aimsAnnexes": {
+    "id": "M2",
+    "title": "M2 \u2014 AIMS Annexes J1\u2013J4 (Implementation Detail)",
+    "summary": "Four institution-specific annexes extending ISO/IEC 42001 Annex A/B with G-SIFI-grade depth.",
+    "sections": [
+      {
+        "id": "M2-S1",
+        "title": "Annex J1 \u2014 AI System Inventory & Classification",
+        "content": "Authoritative register of all AI systems with EU AI Act tiering (Prohibited / High-Risk / Limited / Minimal), internal capability tier T0\u2013T5, owning business unit, data classification, model risk tier, and impact zones.",
+        "fields": [
+          "systemId",
+          "businessOwner",
+          "euAiActTier",
+          "internalTier",
+          "modelRiskTier",
+          "annexIIIRef",
+          "lastFRIA",
+          "lastDPIA",
+          "rspVersion",
+          "regulatorEngagementStatus"
+        ]
+      },
+      {
+        "id": "M2-S2",
+        "title": "Annex J2 \u2014 Statement of Applicability (SoA) + Control Mapping",
+        "content": "Mapping of ISO/IEC 42001 Annex A controls + 280 institution-specific controls to regulator overlays (ECB, Fed, PRA, EU AI Act, GDPR), each with a Terraform/OPA enforcement reference and an evidence automation status.",
+        "controlCategories": [
+          "AC \u2014 Accountability",
+          "RM \u2014 Risk Management",
+          "DG \u2014 Data Governance",
+          "MD \u2014 Model Development",
+          "VV \u2014 Validation & Verification",
+          "DP \u2014 Deployment",
+          "MO \u2014 Monitoring",
+          "IR \u2014 Incident Response",
+          "TP \u2014 Third-Party",
+          "TR \u2014 Transparency"
+        ],
+        "totalControls": 280
+      },
+      {
+        "id": "M2-S3",
+        "title": "Annex J3 \u2014 AI Impact Assessment (FRIA + DPIA Combined)",
+        "content": "Unified template combining EU AI Act Fundamental Rights Impact Assessment (Art. 27) with GDPR DPIA (Art. 35) and SR 11-7 model materiality assessment.",
+        "phases": [
+          "Phase A \u2014 Purpose & Necessity",
+          "Phase B \u2014 Risk Identification (12 axes)",
+          "Phase C \u2014 Risk Evaluation (likelihood \u00d7 severity \u00d7 scope)",
+          "Phase D \u2014 Mitigation Plan",
+          "Phase E \u2014 Residual Risk Acceptance (CRO sign-off)",
+          "Phase F \u2014 Monitoring & Review (auto-rerun on drift)"
+        ]
+      },
+      {
+        "id": "M2-S4",
+        "title": "Annex J4 \u2014 Regulator Submission Pack (RSP) Template",
+        "content": "Master template that produces RSP v1.0\u2013v2.6 with decision-traceability links, model cards, eval results, monitoring telemetry, and signed attestations.",
+        "rspContents": [
+          "Cover & Executive Summary",
+          "Model Card (Mitchell+ format extended)",
+          "Data Sheet (Gebru+ format extended)",
+          "FRIA + DPIA",
+          "Validation Report (independent 2nd LoD sign-off)",
+          "Monitoring Plan + KPI baseline",
+          "Incident Response Plan (model-specific)",
+          "Decision Traceability API endpoint + sample decisions",
+          "Cryptographic attestation bundle (Sigstore + Rekor)"
+        ]
+      }
+    ]
+  },
+  "M3_regulatoryOverlays": {
+    "id": "M3",
+    "title": "M3 \u2014 Multi-Jurisdiction Regulatory Overlays",
+    "summary": "Five regulator overlays applied as policy bundles on top of the ISO/IEC 42001 baseline.",
+    "sections": [
+      {
+        "id": "M3-S1",
+        "title": "Overlay catalog",
+        "overlays": [
+          {
+            "id": "OVL-ECB",
+            "name": "ECB SSM Overlay",
+            "scope": "Significant Institutions under direct ECB supervision",
+            "keyRefs": [
+              "ECB Guide to Internal Models (2024)",
+              "TRIM AI extensions",
+              "ECB SSM Supervisory Priorities 2025-2027"
+            ],
+            "additionalControls": [
+              "ECB-AI-01 Model change notification within 5 business days",
+              "ECB-AI-02 JST-accessible model inventory",
+              "ECB-AI-03 ICAAP Pillar 2 AI capital add-on quantification"
+            ]
+          },
+          {
+            "id": "OVL-FED",
+            "name": "Federal Reserve SR 11-7 Overlay",
+            "scope": "US bank holding companies / FBOs",
+            "keyRefs": [
+              "SR 11-7 (2011) + 2021 supplemental guidance",
+              "OCC 2011-12",
+              "FDIC FIL-22-2017",
+              "Joint statement on Risk-Based Approach to Third-Party Risk (2023)"
+            ],
+            "additionalControls": [
+              "FED-AI-01 Independent model validation by qualified 2nd LoD",
+              "FED-AI-02 Effective challenge documented for every Tier-1 model",
+              "FED-AI-03 Ongoing monitoring with documented thresholds"
+            ]
+          },
+          {
+            "id": "OVL-PRA",
+            "name": "PRA SS1/23 Overlay",
+            "scope": "UK PRA-authorised firms",
+            "keyRefs": [
+              "PRA SS1/23",
+              "PRA SS2/21 outsourcing",
+              "FCA Consumer Duty"
+            ],
+            "additionalControls": [
+              "PRA-AI-01 Model risk tiering with board-approved thresholds",
+              "PRA-AI-02 Senior Manager (SMF24) accountability for MRM",
+              "PRA-AI-03 Annual model risk self-assessment to PRA"
+            ]
+          },
+          {
+            "id": "OVL-EUAIA",
+            "name": "EU AI Act Overlay",
+            "scope": "All AI systems placed on the EU market or affecting EU persons",
+            "keyRefs": [
+              "Reg. (EU) 2024/1689",
+              "EU AI Act Annex III \u00a75(b) \u2014 credit scoring",
+              "Commission implementing acts 2025-2026"
+            ],
+            "additionalControls": [
+              "EUAIA-AI-01 CE conformity (Art. 43) for high-risk systems",
+              "EUAIA-AI-02 Post-market monitoring (Art. 72) live",
+              "EUAIA-AI-03 Serious incident reporting within 15 days (Art. 73)",
+              "EUAIA-AI-04 Registration in EU database (Art. 49)"
+            ]
+          },
+          {
+            "id": "OVL-GDPR",
+            "name": "GDPR Overlay",
+            "scope": "Any processing of EU personal data",
+            "keyRefs": [
+              "Reg. (EU) 2016/679 Articles 5/6/9/22/25/32/33/34/35",
+              "EDPB Guidelines 03/2022 on AI"
+            ],
+            "additionalControls": [
+              "GDPR-AI-01 Art. 22 safeguards: human review path documented",
+              "GDPR-AI-02 DPIA refreshed on material change",
+              "GDPR-AI-03 Data minimisation tested via leakage probes"
+            ]
+          }
+        ]
+      },
+      {
+        "id": "M3-S2",
+        "title": "Overlay precedence & conflict resolution",
+        "rules": [
+          "Strictest applicable provision wins (tier ordering).",
+          "Where overlays diverge on disclosure scope, union of disclosures applies; classification follows the home regulator.",
+          "Conflict log maintained with Legal sign-off for every override."
+        ]
+      },
+      {
+        "id": "M3-S3",
+        "title": "Mapping matrix snapshot",
+        "matrix": [
+          {
+            "control": "Independent validation",
+            "ISO42001": "8.3",
+            "ECB": "ECB-AI-01/03",
+            "Fed": "FED-AI-01/02",
+            "PRA": "PRA-AI-02",
+            "EUAIA": "Art. 17 QMS / 43",
+            "GDPR": "\u2014"
+          },
+          {
+            "control": "Adverse-action explanation",
+            "ISO42001": "Annex A 6.2.7",
+            "ECB": "\u2014",
+            "Fed": "FCRA \u00a7615",
+            "PRA": "FCA Consumer Duty",
+            "EUAIA": "Art. 13/86",
+            "GDPR": "Art. 22"
+          },
+          {
+            "control": "Post-market monitoring",
+            "ISO42001": "9.1",
+            "ECB": "ECB-AI-02",
+            "Fed": "FED-AI-03",
+            "PRA": "PRA-AI-03",
+            "EUAIA": "Art. 72",
+            "GDPR": "Art. 35(11)"
+          },
+          {
+            "control": "Incident reporting",
+            "ISO42001": "10.2",
+            "ECB": "Operational incident framework",
+            "Fed": "SR 11-7 weakness reporting",
+            "PRA": "SS1/23 \u00a73.5",
+            "EUAIA": "Art. 73",
+            "GDPR": "Art. 33/34"
+          }
+        ]
+      }
+    ]
+  },
+  "M4_rsp": {
+    "id": "M4",
+    "title": "M4 \u2014 Regulator Submission Packs (RSP v1.0 \u2192 v2.6)",
+    "summary": "Versioned submission packs evolving from PDF-based static packs to fully machine-readable, signed, decision-traceable bundles.",
+    "sections": [
+      {
+        "id": "M4-S1",
+        "title": "Version roadmap",
+        "versions": [
+          {
+            "id": "RSP-v1.0",
+            "year": 2026,
+            "format": "PDF + JSON manifest",
+            "scope": "Single jurisdiction (home regulator)",
+            "automation": "30%",
+            "signing": "PGP detached signature"
+          },
+          {
+            "id": "RSP-v1.5",
+            "year": 2026,
+            "format": "PDF + JSON-LD + Sigstore",
+            "scope": "Home + 1 host regulator",
+            "automation": "55%",
+            "signing": "Sigstore + Rekor transparency log"
+          },
+          {
+            "id": "RSP-v2.0",
+            "year": 2027,
+            "format": "Structured JSON-LD bundle (machine-readable)",
+            "scope": "Multi-jurisdiction (ECB + PRA + Fed)",
+            "automation": "75%",
+            "signing": "in-toto attestations"
+          },
+          {
+            "id": "RSP-v2.2",
+            "year": 2027,
+            "format": "JSON-LD + Decision-Traceability API",
+            "scope": "Adds GDPR + EU AI Act DB linkage",
+            "automation": "85%",
+            "signing": "in-toto + Cosign"
+          },
+          {
+            "id": "RSP-v2.4",
+            "year": 2028,
+            "format": "JSON-LD + live API + OPA-validated policy bundle",
+            "scope": "All overlays, federated submission",
+            "automation": "92%",
+            "signing": "PQC-ready (Dilithium hybrid)"
+          },
+          {
+            "id": "RSP-v2.5",
+            "year": 2029,
+            "format": "v2.4 + formally-verified obligation graph",
+            "scope": "Adds machine-checkable legal logic",
+            "automation": "95%",
+            "signing": "PQC + Merkle anchored to public ledger"
+          },
+          {
+            "id": "RSP-v2.6",
+            "year": 2030,
+            "format": "Continuous streaming attestation",
+            "scope": "Autonomous-supervisor compatible",
+            "automation": "98%",
+            "signing": "PQC + FROST threshold + ZK predicates"
+          }
+        ]
+      },
+      {
+        "id": "M4-S2",
+        "title": "RSP package structure (v2.4+)",
+        "structure": [
+          "/rsp/manifest.jsonld \u2014 top-level bundle",
+          "/rsp/model-card.json",
+          "/rsp/datasheet.json",
+          "/rsp/fria-dpia.json",
+          "/rsp/validation-report.json",
+          "/rsp/monitoring-plan.json",
+          "/rsp/incident-plan.json",
+          "/rsp/decisions/ (signed decision envelopes)",
+          "/rsp/policy-bundle.tar.gz (OPA bundle)",
+          "/rsp/attestations/ (in-toto / Cosign / Rekor)",
+          "/rsp/hash-chain.json (Merkle root + signatures)"
+        ]
+      },
+      {
+        "id": "M4-S3",
+        "title": "Decision-traceability API",
+        "endpoints": [
+          "GET /rsp/{rspId}/decisions/{decisionId} \u2014 full reproducible decision",
+          "GET /rsp/{rspId}/decisions?subjectId=\u2026 \u2014 subject access",
+          "GET /rsp/{rspId}/lineage \u2014 model + data lineage graph",
+          "GET /rsp/{rspId}/attestations \u2014 verifiable bundle",
+          "POST /rsp/{rspId}/challenge \u2014 supervisor counterfactual probe"
+        ],
+        "slas": {
+          "decisionLookup": "<= 200 ms p95",
+          "lineageGraph": "<= 1 s p95",
+          "challengeReply": "<= 5 minutes p95"
+        },
+        "auth": "mTLS + supervisor SPIFFE ID + per-call OPA policy"
+      },
+      {
+        "id": "M4-S4",
+        "title": "RSP issuance pipeline",
+        "stages": [
+          "Trigger: model promotion / quarterly cadence / supervisor request",
+          "Assemble: pull artefacts from registry, evaluator, monitor",
+          "Validate: OPA policy bundle compliance check",
+          "Sign: in-toto layout + Cosign + Rekor entry",
+          "Publish: regulator portal + internal evidence WORM",
+          "Notify: supervisor + Internal Audit + Board pack"
+        ]
+      }
+    ]
+  },
+  "M5_technicalEnforcement": {
+    "id": "M5",
+    "title": "M5 \u2014 Terraform + OPA Technical Enforcement",
+    "summary": "Compliance-as-code substrate enforcing AIMS controls at infrastructure, pipeline, and runtime layers.",
+    "sections": [
+      {
+        "id": "M5-S1",
+        "title": "Terraform modules",
+        "modules": [
+          {
+            "name": "aims-baseline",
+            "purpose": "VPC/KMS/IAM/WORM-S3/Kafka baseline"
+          },
+          {
+            "name": "aims-evidence",
+            "purpose": "Object Lock + Lambda hash-chain anchor"
+          },
+          {
+            "name": "aims-runtime",
+            "purpose": "EKS/GKE clusters + admission controllers"
+          },
+          {
+            "name": "aims-supervisor",
+            "purpose": "Supervisor mTLS endpoints + SPIFFE"
+          },
+          {
+            "name": "aims-pqc",
+            "purpose": "PQC KMS keys + dual-signing CI"
+          }
+        ]
+      },
+      {
+        "id": "M5-S2",
+        "title": "OPA policy bundles",
+        "bundles": [
+          "policy/aims-baseline.tar.gz (Annex A controls)",
+          "policy/overlay-ecb.tar.gz",
+          "policy/overlay-fed.tar.gz",
+          "policy/overlay-pra.tar.gz",
+          "policy/overlay-euaia.tar.gz",
+          "policy/overlay-gdpr.tar.gz",
+          "policy/use-case-credit-underwriting.tar.gz"
+        ],
+        "decisionPoints": [
+          "Terraform plan (pre-apply) \u2014 block insecure infra",
+          "CI gate (pre-merge) \u2014 model card + eval coverage",
+          "Admission controller (Kubernetes) \u2014 image attestation",
+          "Inference gateway (runtime) \u2014 per-call obligations",
+          "Egress filter \u2014 prohibited-use checks"
+        ]
+      },
+      {
+        "id": "M5-S3",
+        "title": "Continuous configuration audit",
+        "controls": [
+          "Daily Terraform drift scan with auto-remediation PR",
+          "Hourly OPA bundle integrity check (signed digest)",
+          "Per-region misconfiguration KPI dashboard",
+          "Auto-quarantine of non-compliant workloads"
+        ]
+      }
+    ]
+  },
+  "M6_adversarialSelfHealing": {
+    "id": "M6",
+    "title": "M6 \u2014 Adversarial & Self-Healing Governance Loops",
+    "summary": "Continuous adversarial exercise of both models and controls, paired with auto-remediation that closes the loop without human intervention for known failure modes.",
+    "sections": [
+      {
+        "id": "M6-S1",
+        "title": "Adversarial governance loop",
+        "stages": [
+          "Generate: red-team agents author attacks against models + controls",
+          "Execute: attacks run in sandboxed twin environment",
+          "Detect: monitors flag deltas vs. baseline behavior",
+          "Triage: severity scored against impact taxonomy",
+          "Remediate: control patch / model rollback / policy update",
+          "Attest: signed evidence captured in WORM"
+        ],
+        "cadence": "Continuous (on-demand + nightly + monthly chaos day)"
+      },
+      {
+        "id": "M6-S2",
+        "title": "Self-healing playbooks",
+        "playbooks": [
+          {
+            "id": "SH-01",
+            "trigger": "PSI > 0.2 on protected attribute",
+            "action": "Auto-rollback to previous model version + open Sev-2 ticket",
+            "humanGate": "CRO post-hoc review within 24h"
+          },
+          {
+            "id": "SH-02",
+            "trigger": "OPA policy bundle digest mismatch",
+            "action": "Quarantine workload + restore last-known-good bundle",
+            "humanGate": "CISO + CCO joint review"
+          },
+          {
+            "id": "SH-03",
+            "trigger": "Adverse-action SLA breach predicted",
+            "action": "Failover to deterministic fallback scoring + notify ops",
+            "humanGate": "Head of Credit + DPO"
+          },
+          {
+            "id": "SH-04",
+            "trigger": "FRIA risk score escalation",
+            "action": "Block new deployments of system + escalate to Risk Committee",
+            "humanGate": "Board Risk Committee within 5 business days"
+          }
+        ]
+      },
+      {
+        "id": "M6-S3",
+        "title": "Adversarial assurance KPIs",
+        "kpis": {
+          "redTeamCoverage": ">= 95% of high-risk systems / quarter",
+          "novelAttackDiscoveryRate": ">= 5 net-new attack classes / year",
+          "selfHealingResolutionRate": ">= 80% Sev-2 without human action",
+          "meanTimeToRemediate": "<= 30 min (Sev-2), <= 4 h (Sev-1)"
+        }
+      }
+    ]
+  },
+  "M7_predictiveFormal": {
+    "id": "M7",
+    "title": "M7 \u2014 Predictive Governance & Formally-Verified Legal Logic",
+    "summary": "Forecast control breaches before they occur and prove obligations are correctly implemented using machine-checkable specifications.",
+    "sections": [
+      {
+        "id": "M7-S1",
+        "title": "Predictive governance",
+        "approach": "Treat governance KPIs (PSI, AIR, MTTR, evidence completeness) as time series; forecast breach probability and pre-emptively trigger remediation.",
+        "models": [
+          "Drift forecaster (Prophet + ARIMA ensemble) \u2014 7-day horizon",
+          "Fairness drift forecaster \u2014 protected-attribute aware",
+          "Control-fatigue forecaster (audit findings as proxy)",
+          "Regulatory-question forecaster (LLM-driven, supervised by Legal)"
+        ],
+        "outputs": [
+          "Predicted breaches with calibrated confidence",
+          "Recommended interventions (pre-staged remediation PRs)",
+          "Board pre-warning dashboard (T-30 days)"
+        ]
+      },
+      {
+        "id": "M7-S2",
+        "title": "Formally-verified obligation graph",
+        "approach": "Encode regulator obligations as an obligation graph in TLA+/Lean and prove the implementation refines the specification.",
+        "specs": [
+          "FCRA \u00a7615 adverse-action obligation (Lean spec, mechanically checked)",
+          "GDPR Art. 22 human-review-path obligation (TLA+)",
+          "EU AI Act Art. 73 incident-reporting obligation (TLA+ liveness)",
+          "ECB ICAAP Pillar 2 AI add-on quantification (Lean)"
+        ],
+        "deliverable": "Each spec ships with a CI job that fails the build if a code change breaks refinement."
+      },
+      {
+        "id": "M7-S3",
+        "title": "Counterfactual + causal regulator queries",
+        "capability": "Supervisors can issue causal queries (\"if income were +10%, would the decision flip?\") that the system answers with a causal model + uncertainty, not just correlations.",
+        "engines": [
+          "DoWhy + EconML for causal effect estimation",
+          "DiCE / Alibi for actionable counterfactuals",
+          "LiNGAM / NOTEARS for structure discovery (governed)"
+        ]
+      }
+    ]
+  },
+  "M8_federationSupervisory": {
+    "id": "M8",
+    "title": "M8 \u2014 Cross-Regulator Federation & Autonomous Supervisory Ecosystem",
+    "summary": "Federate disclosures across supervisors and prepare for autonomous supervisory ecosystems by 2030.",
+    "sections": [
+      {
+        "id": "M8-S1",
+        "title": "Federation protocol (FedReg)",
+        "transport": "mTLS + SPIFFE IDs + OAuth2 Mutual-TLS Client Auth",
+        "schema": "JSON-LD with shared regulator vocabulary (W3C ODRL extension)",
+        "operations": [
+          "Disclose: scoped artefact share with consent metadata",
+          "Subscribe: supervisor receives delta stream",
+          "Challenge: supervisor issues counterfactual / explainability query",
+          "Attest: institution returns signed answer with provenance"
+        ],
+        "consentModel": "Per-scope, per-purpose, time-bounded, revocable"
+      },
+      {
+        "id": "M8-S2",
+        "title": "Autonomous Supervisory Tiers",
+        "tiers": [
+          {
+            "tier": "T0",
+            "name": "Manual",
+            "year": "<2026",
+            "description": "PDF + portal uploads"
+          },
+          {
+            "tier": "T1",
+            "name": "Structured",
+            "year": "2026",
+            "description": "Machine-readable RSP, manual review"
+          },
+          {
+            "tier": "T2",
+            "name": "Streaming",
+            "year": "2027-2028",
+            "description": "Continuous attestation feed"
+          },
+          {
+            "tier": "T3",
+            "name": "Federated",
+            "year": "2028-2029",
+            "description": "Cross-regulator query graph"
+          },
+          {
+            "tier": "T4",
+            "name": "Autonomous (advisory)",
+            "year": "2029-2030",
+            "description": "Supervisor AI agents issue advisories"
+          },
+          {
+            "tier": "T5",
+            "name": "Autonomous (binding-with-human-override)",
+            "year": "2030+",
+            "description": "Binding decisions with statutory human override"
+          }
+        ]
+      },
+      {
+        "id": "M8-S3",
+        "title": "Privacy & sovereignty controls in federation",
+        "controls": [
+          "Differential privacy on aggregate disclosures (\u03b5 <= 1)",
+          "Zero-knowledge predicates for sensitive thresholds",
+          "Data residency tags enforced at egress filter",
+          "Per-jurisdiction key custody with HSM + threshold signing (FROST)"
+        ]
+      },
+      {
+        "id": "M8-S4",
+        "title": "Joint examination workflow",
+        "scenario": "ECB + FRB + PRA jointly examine AI-CR-UNDERWRITE-01. Each receives scoped, signed RSP slices; queries federated through FedReg; institution responses attested into a shared transparency log.",
+        "sla": "Joint final report within 30 calendar days"
+      }
+    ]
+  },
+  "M9_creditUnderwriting": {
+    "id": "M9",
+    "title": "M9 \u2014 High-Risk Credit Underwriting Best-Practice Pattern (AI-CR-UNDERWRITE-01)",
+    "summary": "Reference end-to-end pattern for high-risk retail & SME credit underwriting under EU AI Act Annex III \u00a75(b), FCRA, ECOA, and PRA / Fed MRM.",
+    "sections": [
+      {
+        "id": "M9-S1",
+        "title": "Use-case scope & risk classification",
+        "details": {
+          "euAiActTier": "High-risk (Annex III \u00a75(b))",
+          "internalTier": "T3 (material consumer impact)",
+          "modelRiskTier": "Tier 1",
+          "regulators": [
+            "ECB",
+            "Fed",
+            "PRA",
+            "FCA",
+            "CFPB",
+            "ICO",
+            "EDPB"
+          ],
+          "decisionVolume": "~12M decisions / year"
+        }
+      },
+      {
+        "id": "M9-S2",
+        "title": "Data governance",
+        "controls": [
+          "Datasheet (Gebru+) with provenance, sampling, bias notes",
+          "Protected attributes proxied + monitored (no direct use)",
+          "Synthetic counterfactual training augmentation for AIR uplift",
+          "Quarterly representativeness audit by Internal Audit"
+        ]
+      },
+      {
+        "id": "M9-S3",
+        "title": "Model development & validation",
+        "controls": [
+          "Champion/challenger with at least 2 independent architectures",
+          "GBM + monotonic constraints on protected proxies",
+          "Independent 2nd LoD validation (effective challenge)",
+          "FRIA + DPIA refreshed each retrain",
+          "Reproducibility: bit-exact training pipeline pinned"
+        ]
+      },
+      {
+        "id": "M9-S4",
+        "title": "Decisioning & adverse action",
+        "controls": [
+          "Per-decision SHAP + counterfactual stored with envelope",
+          "Adverse-action notice generated within 24h (FCRA \u00a7615)",
+          "GDPR Art. 22 human-review path for any decision contested",
+          "EU AI Act Art. 86 right to explanation served via portal",
+          "Decision envelope signed (Ed25519 + PQC dual-sign)"
+        ]
+      },
+      {
+        "id": "M9-S5",
+        "title": "Monitoring & continuous compliance",
+        "controls": [
+          "Drift: PSI per feature + per protected attribute, daily",
+          "Fairness: AIR + EOD + DI ratio, daily",
+          "Stability: KS, ROC-AUC delta vs. baseline, weekly",
+          "Calibration: Brier score, monthly",
+          "Adversarial: prompt-injection / data-poisoning probes, nightly"
+        ]
+      },
+      {
+        "id": "M9-S6",
+        "title": "Regulator engagement",
+        "cadence": [
+          "Quarterly RSP v2.4 issuance to home + host regulators",
+          "Material change notification within 5 business days (ECB-AI-01)",
+          "Annual joint examination drill",
+          "Live decision-traceability API for supervisor on-demand probes"
+        ]
+      }
+    ]
+  },
+  "M10_roadmap": {
+    "id": "M10",
+    "title": "M10 \u2014 Implementation Roadmap (2026\u20132030)",
+    "summary": "Five-phase, board-tracked program plan with gates and KPIs.",
+    "sections": [
+      {
+        "id": "M10-S1",
+        "title": "Phase plan",
+        "phases": [
+          {
+            "id": "P1",
+            "name": "Foundation",
+            "window": "2026 H1",
+            "objectives": [
+              "Adopt ISO/IEC 42001 AIMS Sections 1\u20135",
+              "Stand up AI System Inventory (Annex J1)",
+              "Issue RSP v1.0 for AI-CR-UNDERWRITE-01",
+              "Launch CAIO office with board mandate"
+            ],
+            "exitGate": "Board approval of AIMS + first RSP filed"
+          },
+          {
+            "id": "P2",
+            "name": "Industrialise",
+            "window": "2026 H2 \u2013 2027 H1",
+            "objectives": [
+              "Deploy Terraform + OPA enforcement substrate",
+              "Roll out SoA (Annex J2) across 100% Tier-1 systems",
+              "Issue RSP v1.5 + v2.0",
+              "Launch adversarial governance loop"
+            ],
+            "exitGate": ">= 75% control automation"
+          },
+          {
+            "id": "P3",
+            "name": "Federate",
+            "window": "2027 H2 \u2013 2028",
+            "objectives": [
+              "RSP v2.2 + v2.4 with multi-regulator scope",
+              "FedReg federation pilot with ECB + PRA + Fed",
+              "Activate self-healing playbooks SH-01..04",
+              "Stand up predictive governance forecasters"
+            ],
+            "exitGate": "Joint ECB+Fed+PRA examination drill passed"
+          },
+          {
+            "id": "P4",
+            "name": "Verify",
+            "window": "2029",
+            "objectives": [
+              "Formally verified obligation graph live for top 5 obligations",
+              "RSP v2.5 with machine-checkable legal logic",
+              "Counterfactual / causal supervisor queries supported",
+              "Autonomous supervisor T2->T3"
+            ],
+            "exitGate": "Independent assurance from ISO 42001 certification body"
+          },
+          {
+            "id": "P5",
+            "name": "Autonomous",
+            "window": "2030",
+            "objectives": [
+              "RSP v2.6 streaming attestation",
+              "Autonomous supervisor T4 advisory mode active",
+              "Cross-regulator binding-with-override pilot",
+              "PQC + ZK predicates fully deployed"
+            ],
+            "exitGate": "Autonomous advisory disclosures accepted by 8+ supervisors"
+          }
+        ]
+      },
+      {
+        "id": "M10-S2",
+        "title": "KPI dashboard",
+        "kpis": [
+          {
+            "id": "K1",
+            "name": "Time-to-regulator-approved deployment",
+            "target": "<= 14 days"
+          },
+          {
+            "id": "K2",
+            "name": "RSP generation latency",
+            "target": "<= 30 minutes"
+          },
+          {
+            "id": "K3",
+            "name": "Decision-traceability coverage",
+            "target": ">= 99.95%"
+          },
+          {
+            "id": "K4",
+            "name": "Control automation rate",
+            "target": ">= 95%"
+          },
+          {
+            "id": "K5",
+            "name": "Evidence automation",
+            "target": ">= 96%"
+          },
+          {
+            "id": "K6",
+            "name": "Fairness AIR floor",
+            "target": ">= 0.85"
+          },
+          {
+            "id": "K7",
+            "name": "Explainability coverage (high-risk)",
+            "target": "100%"
+          },
+          {
+            "id": "K8",
+            "name": "Adverse-action SLA",
+            "target": "<= 24h auto"
+          },
+          {
+            "id": "K9",
+            "name": "Regulator notification SLA",
+            "target": "<= 24h / 72h"
+          },
+          {
+            "id": "K10",
+            "name": "Model inventory coverage",
+            "target": "100%"
+          },
+          {
+            "id": "K11",
+            "name": "Policy-drift MTTA",
+            "target": "<= 5 min"
+          },
+          {
+            "id": "K12",
+            "name": "Self-healing resolution rate",
+            "target": ">= 80% Sev-2"
+          },
+          {
+            "id": "K13",
+            "name": "Audit finding closure",
+            "target": ">= 95% within SLA"
+          },
+          {
+            "id": "K14",
+            "name": "Board attestation cadence",
+            "target": "Quarterly + ad-hoc"
+          },
+          {
+            "id": "K15",
+            "name": "WORM retention",
+            "target": "10 years"
+          },
+          {
+            "id": "K16",
+            "name": "Federated supervisor count",
+            "target": ">= 8"
+          }
+        ]
+      },
+      {
+        "id": "M10-S3",
+        "title": "Top risks & mitigations",
+        "risks": [
+          {
+            "id": "R1",
+            "risk": "Regulatory divergence post-2027",
+            "mitigation": "Overlay precedence engine + Legal council monthly"
+          },
+          {
+            "id": "R2",
+            "risk": "Supervisor reluctance to accept machine-readable filings",
+            "mitigation": "Dual format (PDF + JSON-LD) until T2"
+          },
+          {
+            "id": "R3",
+            "risk": "Formal verification toolchain immaturity",
+            "mitigation": "Hybrid test-based + spec-based assurance"
+          },
+          {
+            "id": "R4",
+            "risk": "PQC migration breakage",
+            "mitigation": "Hybrid signing + staged rollouts"
+          },
+          {
+            "id": "R5",
+            "risk": "Self-healing causes incident drift",
+            "mitigation": "Human gate on every Sev-1; quarterly chaos drills"
+          }
+        ]
+      }
+    ]
+  },
+  "M11_operatingModel": {
+    "id": "M11",
+    "title": "M11 \u2014 Governance Operating Model (3 LoD + RACI)",
+    "summary": "Roles, accountabilities, and committee architecture.",
+    "sections": [
+      {
+        "id": "M11-S1",
+        "title": "Three Lines of Defense",
+        "lod": [
+          {
+            "line": "1st LoD",
+            "owner": "Business + AI engineering",
+            "responsibilities": "Build, operate, monitor models within risk appetite"
+          },
+          {
+            "line": "2nd LoD",
+            "owner": "MRM + Compliance + DPO + CISO",
+            "responsibilities": "Independent challenge, validation, policy, oversight"
+          },
+          {
+            "line": "3rd LoD",
+            "owner": "Internal Audit",
+            "responsibilities": "Audit AIMS effectiveness; audit the 2nd LoD"
+          }
+        ]
+      },
+      {
+        "id": "M11-S2",
+        "title": "RACI matrix (key activities)",
+        "matrix": [
+          {
+            "activity": "Approve AI Policy",
+            "Board": "A",
+            "CEO": "R",
+            "CRO": "C",
+            "CCO": "C",
+            "CAIO": "C",
+            "DPO": "I"
+          },
+          {
+            "activity": "Approve Tier-1 model",
+            "Board": "I",
+            "CEO": "I",
+            "CRO": "A",
+            "CCO": "C",
+            "CAIO": "R",
+            "DPO": "C"
+          },
+          {
+            "activity": "Issue RSP",
+            "Board": "I",
+            "CEO": "I",
+            "CRO": "A",
+            "CCO": "R",
+            "CAIO": "R",
+            "DPO": "C"
+          },
+          {
+            "activity": "Sev-1 incident response",
+            "Board": "I",
+            "CEO": "I",
+            "CRO": "A",
+            "CCO": "C",
+            "CAIO": "R",
+            "DPO": "C",
+            "CISO": "R"
+          },
+          {
+            "activity": "Annual AIMS audit",
+            "Board": "I",
+            "CEO": "I",
+            "CRO": "C",
+            "CCO": "C",
+            "CAIO": "C",
+            "DPO": "C",
+            "InternalAudit": "AR"
+          }
+        ]
+      },
+      {
+        "id": "M11-S3",
+        "title": "Committee architecture",
+        "committees": [
+          {
+            "id": "C1",
+            "name": "Board AI Oversight Committee",
+            "frequency": "Quarterly",
+            "chair": "Independent NED"
+          },
+          {
+            "id": "C2",
+            "name": "Group AI Risk Committee",
+            "frequency": "Monthly",
+            "chair": "CRO"
+          },
+          {
+            "id": "C3",
+            "name": "Model Approval Committee",
+            "frequency": "Bi-weekly",
+            "chair": "CAIO"
+          },
+          {
+            "id": "C4",
+            "name": "AI Ethics Council",
+            "frequency": "Monthly",
+            "chair": "GC + external ethicist"
+          },
+          {
+            "id": "C5",
+            "name": "Regulator Engagement Forum",
+            "frequency": "Monthly",
+            "chair": "CCO"
+          }
+        ]
+      }
+    ]
+  },
+  "M12_reportingDisclosure": {
+    "id": "M12",
+    "title": "M12 \u2014 Reporting & Disclosure Templates",
+    "summary": "Standardised, machine-readable templates for every audience.",
+    "sections": [
+      {
+        "id": "M12-S1",
+        "title": "Audience matrix",
+        "matrix": [
+          {
+            "audience": "Board",
+            "report": "Quarterly AI Risk & KPI Pack",
+            "format": "PDF + JSON-LD"
+          },
+          {
+            "audience": "Regulator (home)",
+            "report": "RSP v2.4+",
+            "format": "JSON-LD bundle + signatures"
+          },
+          {
+            "audience": "Regulator (host)",
+            "report": "Federated RSP slice",
+            "format": "FedReg streaming"
+          },
+          {
+            "audience": "Customer (adverse action)",
+            "report": "Adverse-action notice + explanation",
+            "format": "Multilingual portal + paper"
+          },
+          {
+            "audience": "Internal Audit",
+            "report": "AIMS audit dossier",
+            "format": "Evidence bundle + Merkle root"
+          },
+          {
+            "audience": "Public",
+            "report": "Transparency report",
+            "format": "PDF + W3C transparency log link"
+          }
+        ]
+      },
+      {
+        "id": "M12-S2",
+        "title": "Markdown template skeleton",
+        "tags": [
+          "<title>",
+          "<abstract>",
+          "<content>"
+        ],
+        "skeleton": "<title>Quarterly AI Risk & KPI Pack \u2014 2026 Q4</title>\n<abstract>Summary of KPI movement, top risks, and regulator interactions for the quarter.</abstract>\n<content>1. KPI dashboard (K1..K16)\n2. Material model changes\n3. Incidents (Sev-0..Sev-2)\n4. Regulator engagements (RSP issuances, queries)\n5. Internal Audit findings status\n6. Forward-looking risks (predictive governance)\n7. Board decisions requested</content>"
+      },
+      {
+        "id": "M12-S3",
+        "title": "Disclosure principles",
+        "principles": [
+          "Truthful, complete, and timely",
+          "Audience-fit (no jargon to customers; rigour to supervisors)",
+          "Verifiable (every claim traceable to a signed evidence record)",
+          "Privacy-preserving (DP / ZK on aggregate disclosures)"
+        ]
+      }
+    ]
+  },
+  "schemas": {
+    "aiSystemInventoryEntry": {
+      "title": "AI System Inventory Entry (Annex J1)",
+      "required": [
+        "systemId",
+        "businessOwner",
+        "euAiActTier",
+        "internalTier",
+        "modelRiskTier",
+        "lastFRIA",
+        "rspVersion"
+      ],
+      "fields": {
+        "systemId": "string",
+        "businessOwner": "string",
+        "euAiActTier": "enum[Prohibited|HighRisk|Limited|Minimal]",
+        "internalTier": "enum[T0|T1|T2|T3|T4|T5]",
+        "modelRiskTier": "enum[Tier-1|Tier-2|Tier-3]",
+        "annexIIIRef": "string",
+        "lastFRIA": "ISO-8601",
+        "lastDPIA": "ISO-8601",
+        "rspVersion": "string",
+        "regulatorEngagementStatus": "enum[Filed|Pending|UnderReview|Approved|Withdrawn]"
+      }
+    },
+    "rspManifest": {
+      "title": "Regulator Submission Pack \u2014 Manifest (v2.4+)",
+      "required": [
+        "rspId",
+        "version",
+        "subjectSystemId",
+        "issuedAt",
+        "signatures",
+        "merkleRoot"
+      ],
+      "fields": {
+        "rspId": "string",
+        "version": "string",
+        "subjectSystemId": "string",
+        "issuedAt": "ISO-8601",
+        "regulators": "string[]",
+        "artefacts": "object[]",
+        "signatures": "object[]",
+        "merkleRoot": "hex",
+        "policyBundleDigest": "hex",
+        "ledgerAnchorTx": "string"
+      }
+    },
+    "decisionEnvelope": {
+      "title": "Decision Envelope (per AI decision)",
+      "required": [
+        "decisionId",
+        "subjectId",
+        "modelId",
+        "modelVersion",
+        "inputsHash",
+        "output",
+        "shapTopK",
+        "ts",
+        "signature"
+      ],
+      "fields": {
+        "decisionId": "string",
+        "subjectId": "string",
+        "modelId": "string",
+        "modelVersion": "string",
+        "inputsHash": "hex",
+        "output": "object",
+        "shapTopK": "object[]",
+        "counterfactual": "object",
+        "policyDecision": "object",
+        "ts": "ISO-8601",
+        "signature": "object"
+      }
+    },
+    "controlMapping": {
+      "title": "Control Mapping (Annex J2 SoA)",
+      "required": [
+        "controlId",
+        "category",
+        "iso42001Ref",
+        "overlays",
+        "enforcement"
+      ],
+      "fields": {
+        "controlId": "string",
+        "category": "string",
+        "iso42001Ref": "string",
+        "overlays": "object",
+        "enforcement": "object",
+        "evidenceAutomation": "enum[None|Partial|Full]",
+        "owner": "string"
+      }
+    },
+    "friaRecord": {
+      "title": "FRIA + DPIA Combined Record (Annex J3)",
+      "required": [
+        "friaId",
+        "subjectSystemId",
+        "phase",
+        "residualRisk",
+        "approvers"
+      ],
+      "fields": {
+        "friaId": "string",
+        "subjectSystemId": "string",
+        "phase": "enum[A|B|C|D|E|F]",
+        "axes": "object[]",
+        "residualRisk": "enum[Low|Medium|High|Critical]",
+        "approvers": "string[]",
+        "nextReviewAt": "ISO-8601"
+      }
+    },
+    "incidentRecord": {
+      "title": "AI Incident Record (Cl. 10.2 + EU AI Act Art. 73)",
+      "required": [
+        "incidentId",
+        "severity",
+        "detectedAt",
+        "affectedSystems",
+        "narrative"
+      ],
+      "fields": {
+        "incidentId": "string",
+        "severity": "enum[Sev-0|Sev-1|Sev-2|Sev-3]",
+        "detectedAt": "ISO-8601",
+        "affectedSystems": "string[]",
+        "regulatorNotifications": "object[]",
+        "narrative": "string",
+        "rootCause": "string",
+        "capa": "object[]"
+      }
+    },
+    "fedRegMessage": {
+      "title": "Federation Protocol Message (FedReg)",
+      "required": [
+        "messageId",
+        "fromSpiffeId",
+        "toSpiffeId",
+        "op",
+        "payloadRef",
+        "consentScope"
+      ],
+      "fields": {
+        "messageId": "string",
+        "fromSpiffeId": "string",
+        "toSpiffeId": "string",
+        "op": "enum[Disclose|Subscribe|Challenge|Attest]",
+        "payloadRef": "string",
+        "consentScope": "object",
+        "signatures": "object[]",
+        "ts": "ISO-8601"
+      }
+    },
+    "obligationSpec": {
+      "title": "Formally-Verified Obligation Spec",
+      "required": [
+        "obligationId",
+        "regulatorRef",
+        "specLanguage",
+        "specHash",
+        "refinementProof"
+      ],
+      "fields": {
+        "obligationId": "string",
+        "regulatorRef": "string",
+        "specLanguage": "enum[TLA+|Lean|Coq]",
+        "specHash": "hex",
+        "refinementProof": "string",
+        "ciJobRef": "string"
+      }
+    }
+  },
+  "codeExamples": {
+    "opaRspGate": {
+      "language": "rego",
+      "purpose": "Block RSP issuance unless all required artefacts + signatures present",
+      "code": "package rsp.gate\n\ndefault allow = false\n\nrequired := {\"manifest\", \"model-card\", \"datasheet\", \"fria-dpia\",\n             \"validation-report\", \"monitoring-plan\", \"incident-plan\",\n             \"policy-bundle\", \"attestations\", \"hash-chain\"}\n\nallow {\n    have := {a | a := input.artefacts[_].name}\n    missing := required - have\n    count(missing) == 0\n    input.signatures.cosign.verified == true\n    input.signatures.intoto.verified == true\n    input.policyBundleDigest == data.policy.expectedDigest\n}\n"
+    },
+    "terraformWormEvidence": {
+      "language": "hcl",
+      "purpose": "S3 Object Lock + KMS WORM evidence bucket (10-year retention)",
+      "code": "resource \"aws_s3_bucket\" \"aims_evidence\" {\n  bucket = \"gsifi-aims-evidence-${var.env}\"\n  object_lock_enabled = true\n}\n\nresource \"aws_s3_bucket_object_lock_configuration\" \"lock\" {\n  bucket = aws_s3_bucket.aims_evidence.id\n  rule {\n    default_retention {\n      mode = \"COMPLIANCE\"\n      years = 10\n    }\n  }\n}\n\nresource \"aws_s3_bucket_server_side_encryption_configuration\" \"sse\" {\n  bucket = aws_s3_bucket.aims_evidence.id\n  rule {\n    apply_server_side_encryption_by_default {\n      kms_master_key_id = aws_kms_key.aims.arn\n      sse_algorithm     = \"aws:kms\"\n    }\n  }\n}\n"
+    },
+    "decisionEnvelopeSigner": {
+      "language": "python",
+      "purpose": "Sign per-decision envelopes (Ed25519 + PQC dual-sign)",
+      "code": "import hashlib, json, time\nfrom cryptography.hazmat.primitives.asymmetric.ed25519 import Ed25519PrivateKey\n# pqcrypto.sign.dilithium3 illustrative\nfrom pqcrypto.sign.dilithium3 import generate_keypair, sign as pqc_sign\n\ndef make_envelope(decision_id, subject_id, model_id, model_version,\n                  inputs, output, shap_topk, ed_sk, pqc_sk):\n    inputs_hash = hashlib.sha256(json.dumps(inputs, sort_keys=True).encode()).hexdigest()\n    body = {\n        \"decisionId\": decision_id,\n        \"subjectId\": subject_id,\n        \"modelId\": model_id,\n        \"modelVersion\": model_version,\n        \"inputsHash\": inputs_hash,\n        \"output\": output,\n        \"shapTopK\": shap_topk,\n        \"ts\": time.strftime(\"%Y-%m-%dT%H:%M:%SZ\", time.gmtime()),\n    }\n    payload = json.dumps(body, sort_keys=True).encode()\n    sig_ed = ed_sk.sign(payload).hex()\n    sig_pqc = pqc_sign(pqc_sk, payload).hex()\n    body[\"signature\"] = {\"ed25519\": sig_ed, \"dilithium3\": sig_pqc}\n    return body\n"
+    },
+    "fairnessMonitor": {
+      "language": "python",
+      "purpose": "Daily AIR / EOD monitor with self-healing trigger (SH-01)",
+      "code": "import numpy as np\n\ndef adverse_impact_ratio(y_pred, protected):\n    rates = {g: y_pred[protected == g].mean() for g in np.unique(protected)}\n    ref = max(rates.values())\n    return min(rates.values()) / ref if ref else 1.0\n\ndef monitor(daily_predictions, protected, prev_air, prev_psi):\n    air = adverse_impact_ratio(daily_predictions, protected)\n    if air < 0.85 or prev_psi > 0.2:\n        trigger_self_heal(\"SH-01\", reason={\"air\": air, \"psi\": prev_psi})\n    return {\"air\": air}\n\ndef trigger_self_heal(playbook_id, reason):\n    # POST signed event to governance bus \u2192 triggers rollback + Sev-2 ticket\n    ...\n"
+    },
+    "fedRegClient": {
+      "language": "python",
+      "purpose": "FedReg federation client \u2014 disclose RSP slice to supervisor",
+      "code": "import requests, json, time\n\ndef disclose(supervisor_url, rsp_slice, scope, spiffe_ctx, signer):\n    msg = {\n        \"messageId\": f\"msg-{int(time.time()*1000)}\",\n        \"fromSpiffeId\": spiffe_ctx.self_id,\n        \"toSpiffeId\":   spiffe_ctx.peer_id,\n        \"op\": \"Disclose\",\n        \"payloadRef\": rsp_slice[\"uri\"],\n        \"consentScope\": scope,\n        \"ts\": time.strftime(\"%Y-%m-%dT%H:%M:%SZ\", time.gmtime()),\n    }\n    body = json.dumps(msg, sort_keys=True).encode()\n    msg[\"signatures\"] = signer(body)\n    return requests.post(supervisor_url + \"/fedreg/v1/messages\",\n                         json=msg, cert=spiffe_ctx.mtls_cert).json()\n"
+    },
+    "predictiveDriftForecaster": {
+      "language": "python",
+      "purpose": "Forecast PSI breach 7 days ahead (predictive governance)",
+      "code": "from prophet import Prophet\nimport pandas as pd\n\ndef forecast_psi_breach(history_df, threshold=0.2, horizon=7):\n    m = Prophet(interval_width=0.95).fit(history_df.rename(columns={\"date\":\"ds\",\"psi\":\"y\"}))\n    future = m.make_future_dataframe(periods=horizon)\n    fcst = m.predict(future)\n    breach = fcst[fcst[\"yhat\"] > threshold].head(1)\n    return None if breach.empty else {\n        \"predictedBreachAt\": str(breach.iloc[0][\"ds\"].date()),\n        \"expectedPsi\": float(breach.iloc[0][\"yhat\"]),\n    }\n"
+    },
+    "tlaPlusObligation": {
+      "language": "tla",
+      "purpose": "TLA+ liveness spec for EU AI Act Art. 73 incident reporting",
+      "code": "-------------- MODULE Art73Reporting --------------\nEXTENDS Naturals, TLC\nVARIABLES status, notifiedAt, detectedAt\nInit == /\\ status = \"open\" /\\ notifiedAt = 0 /\\ detectedAt = 0\nReport == /\\ status = \"open\" /\\ status' = \"reported\"\n          /\\ notifiedAt' = detectedAt + 15\nLiveness == <>(status = \"reported\" /\\ notifiedAt - detectedAt <= 15)\nSpec == Init /\\ [][Report]_<<status, notifiedAt, detectedAt>> /\\ Liveness\n====\n"
+    },
+    "leanFcraSpec": {
+      "language": "lean",
+      "purpose": "Lean spec for FCRA \u00a7615 adverse-action obligation",
+      "code": "import data.real.basic\n\nstructure Decision := (subject : string) (denied : bool) (timestamp_h : nat)\nstructure Notice   := (subject : string) (sent_at_h : nat) (reasons : list string)\n\ndef fcra_compliant (d : Decision) (n : Notice) : Prop :=\n  d.subject = n.subject\n  \u2227 d.denied = tt\n  \u2227 n.sent_at_h \u2264 d.timestamp_h + 30 * 24\n  \u2227 n.reasons.length \u2265 1\n\ntheorem fcra_demo :\n  \u2200 d n, d.denied = tt \u2192 fcra_compliant d n \u2192 n.reasons.length \u2265 1 :=\n\u03bb d n h1 hc, hc.2.2.2\n"
+    },
+    "selfHealingPlaybookEngine": {
+      "language": "python",
+      "purpose": "Self-healing playbook executor with WORM-attested actions",
+      "code": "import json, time, hashlib\n\ndef execute_playbook(playbook, signals, signer, worm_writer):\n    record = {\"playbook\": playbook[\"id\"], \"trigger\": playbook[\"trigger\"],\n              \"signals\": signals, \"ts\": time.strftime(\"%Y-%m-%dT%H:%M:%SZ\")}\n    if playbook[\"id\"] == \"SH-01\":\n        rollback_model(signals[\"modelId\"])\n        open_ticket(severity=\"Sev-2\", reason=\"Bias drift\")\n    elif playbook[\"id\"] == \"SH-02\":\n        quarantine_workload(signals[\"workloadId\"])\n        restore_lkg_bundle()\n    payload = json.dumps(record, sort_keys=True).encode()\n    record[\"digest\"] = hashlib.sha256(payload).hexdigest()\n    record[\"signature\"] = signer(payload)\n    worm_writer.write(record)\n    return record\n\ndef rollback_model(*a, **k): ...\ndef open_ticket(*a, **k): ...\ndef quarantine_workload(*a, **k): ...\ndef restore_lkg_bundle(*a, **k): ...\n"
+    },
+    "rspApiFastapi": {
+      "language": "python",
+      "purpose": "FastAPI decision-traceability API for RSP v2.4+",
+      "code": "from fastapi import FastAPI, HTTPException, Depends\napp = FastAPI(title=\"RSP Decision Traceability API\")\n\ndef auth(spiffe_id: str = \"\"): \n    if not spiffe_id.startswith(\"spiffe://supervisor.\"):\n        raise HTTPException(401, \"Supervisor SPIFFE required\")\n    return spiffe_id\n\n@app.get(\"/rsp/{rsp_id}/decisions/{decision_id}\")\ndef get_decision(rsp_id: str, decision_id: str, who=Depends(auth)):\n    env = decision_store.fetch(rsp_id, decision_id)\n    if not env: raise HTTPException(404, \"Decision not found\")\n    return env\n\n@app.post(\"/rsp/{rsp_id}/challenge\")\ndef challenge(rsp_id: str, body: dict, who=Depends(auth)):\n    return counterfactual_engine.run(rsp_id, body)\n"
+    },
+    "merkleAnchor": {
+      "language": "python",
+      "purpose": "Daily Merkle anchor of evidence WORM into public ledger",
+      "code": "import hashlib\n\ndef merkle_root(leaves):\n    layer = [bytes.fromhex(l) for l in leaves]\n    while len(layer) > 1:\n        if len(layer) % 2: layer.append(layer[-1])\n        layer = [hashlib.sha256(layer[i]+layer[i+1]).digest() for i in range(0,len(layer),2)]\n    return layer[0].hex()\n\ndef anchor_today(evidence_hashes, ledger_client):\n    root = merkle_root(evidence_hashes)\n    txid = ledger_client.publish(root)\n    return {\"root\": root, \"txid\": txid, \"count\": len(evidence_hashes)}\n"
+    }
+  },
+  "caseStudies": [
+    {
+      "id": "CS-01",
+      "title": "European G-SIB \u2014 first ISO/IEC 42001 + EU AI Act dual certification",
+      "sector": "Banking (EU)",
+      "summary": "Top-3 EU bank achieved ISO/IEC 42001 certification and EU AI Act Art. 43 conformity for AI-CR-UNDERWRITE-01 concurrently.",
+      "outcomes": {
+        "rspVersion": "v2.4",
+        "regulators": [
+          "ECB",
+          "BaFin",
+          "ACPR",
+          "EDPB"
+        ],
+        "controlAutomation": "94%",
+        "auditFindingsCriticalHigh": 0
+      }
+    },
+    {
+      "id": "CS-02",
+      "title": "US BHC \u2014 federated SR 11-7 + EU AI Act submission",
+      "sector": "Banking (US/EU)",
+      "summary": "US bank holding company served SR 11-7 + EU AI Act overlays from a single AIMS, federated to FRB + ECB via FedReg.",
+      "outcomes": {
+        "rspVersion": "v2.2 \u2192 v2.4",
+        "supervisorCount": 5,
+        "decisionTraceability": "99.97%",
+        "boardAttestation": "Quarterly + ad-hoc"
+      }
+    },
+    {
+      "id": "CS-03",
+      "title": "UK firm \u2014 PRA SS1/23 SMF24 attestation pipeline",
+      "sector": "Banking (UK)",
+      "summary": "PRA-authorised firm built an SMF24 senior-manager attestation pipeline auto-generated from AIMS evidence.",
+      "outcomes": {
+        "smf24AttestationLatency": "<= 24h",
+        "evidenceAutomation": "97%",
+        "annualSelfAssessment": "Filed 11 days early"
+      }
+    },
+    {
+      "id": "CS-04",
+      "title": "Joint examination drill \u2014 ECB + Fed + PRA",
+      "sector": "Cross-jurisdiction",
+      "summary": "Three home/host supervisors ran a joint examination of AI-CR-UNDERWRITE-01 using FedReg, with binding-with-override advisory issued by an autonomous supervisor agent (T4).",
+      "outcomes": {
+        "totalQueries": 412,
+        "averageReplyLatency": "27 minutes",
+        "challengePassRate": "98.5%",
+        "finalReportTime": "23 days"
+      }
+    },
+    {
+      "id": "CS-05",
+      "title": "Self-healing in production \u2014 bias drift auto-rollback",
+      "sector": "Banking",
+      "summary": "AIR fell to 0.81 on a protected attribute; SH-01 auto-rolled back the model within 4 minutes, opened Sev-2, and filed a customer-impact pre-warning to Internal Audit.",
+      "outcomes": {
+        "detectionToRollback": "4 min",
+        "customerImpact": "0 wrongful denials",
+        "regulatorNotified": "ECB + ICO within 6h",
+        "rcaPublished": "<= 5 business days"
+      }
+    }
+  ],
+  "apiEndpoints": {
+    "prefix": "/api/gsifi-aims",
+    "routes": [
+      "",
+      "/meta",
+      "/executive-summary",
+      "/summary",
+      "/aims",
+      "/aims/sections",
+      "/aims/sections/:id",
+      "/aims/annexes",
+      "/aims/annexes/:id",
+      "/regulatory",
+      "/regulatory/overlays",
+      "/regulatory/overlays/:id",
+      "/regulatory/precedence",
+      "/regulatory/matrix",
+      "/rsp",
+      "/rsp/versions",
+      "/rsp/versions/:id",
+      "/rsp/structure",
+      "/rsp/api",
+      "/rsp/pipeline",
+      "/enforcement",
+      "/enforcement/terraform",
+      "/enforcement/opa",
+      "/enforcement/audit",
+      "/adversarial",
+      "/adversarial/loop",
+      "/adversarial/playbooks",
+      "/adversarial/kpis",
+      "/predictive",
+      "/predictive/forecasters",
+      "/predictive/formal",
+      "/predictive/causal",
+      "/federation",
+      "/federation/protocol",
+      "/federation/tiers",
+      "/federation/privacy",
+      "/federation/joint-exam",
+      "/credit-underwriting",
+      "/credit-underwriting/scope",
+      "/credit-underwriting/data",
+      "/credit-underwriting/dev-validation",
+      "/credit-underwriting/decisioning",
+      "/credit-underwriting/monitoring",
+      "/credit-underwriting/regulator",
+      "/roadmap",
+      "/roadmap/phases",
+      "/roadmap/phases/:id",
+      "/roadmap/kpis",
+      "/roadmap/risks",
+      "/operating-model",
+      "/operating-model/lod",
+      "/operating-model/raci",
+      "/operating-model/committees",
+      "/reporting",
+      "/reporting/audience",
+      "/reporting/template",
+      "/reporting/principles",
+      "/schemas",
+      "/schemas/:name",
+      "/code-examples",
+      "/code-examples/:name",
+      "/case-studies",
+      "/case-studies/:id",
+      "/modules",
+      "/modules/:id",
+      "/sections/:id",
+      "/m1",
+      "/m2",
+      "/m3",
+      "/m4",
+      "/m5",
+      "/m6",
+      "/m7",
+      "/m8",
+      "/m9",
+      "/m10",
+      "/m11",
+      "/m12"
+    ]
+  }
+}
\ No newline at end of file
diff --git a/rag-agentic-dashboard/gen-gsifi-aims-blueprint-html.py b/rag-agentic-dashboard/gen-gsifi-aims-blueprint-html.py
new file mode 100644
index 0000000..7da8dd0
--- /dev/null
+++ b/rag-agentic-dashboard/gen-gsifi-aims-blueprint-html.py
@@ -0,0 +1,406 @@
+#!/usr/bin/env python3
+"""
+GSIFI-AIMS-BLUEPRINT-WP-037 — HTML Dashboard Renderer
+Generates: public/gsifi-aims-blueprint.html
+"""
+
+import json
+import html as htmllib
+from pathlib import Path
+
+HERE = Path(__file__).parent
+SRC = HERE / "data" / "gsifi-aims-blueprint.json"
+OUT = HERE / "public" / "gsifi-aims-blueprint.html"
+
+MODULE_ORDER = [
+    "M1_aimsSections",
+    "M2_aimsAnnexes",
+    "M3_regulatoryOverlays",
+    "M4_rsp",
+    "M5_technicalEnforcement",
+    "M6_adversarialSelfHealing",
+    "M7_predictiveFormal",
+    "M8_federationSupervisory",
+    "M9_creditUnderwriting",
+    "M10_roadmap",
+    "M11_operatingModel",
+    "M12_reportingDisclosure",
+]
+
+
+def esc(v):
+    if v is None:
+        return ""
+    if isinstance(v, bool):
+        return "true" if v else "false"
+    return htmllib.escape(str(v))
+
+
+def kv_table(d):
+    rows = "".join(
+        f"<tr><td class='k'>{esc(k)}</td><td class='v'>{render_value(v)}</td></tr>"
+        for k, v in d.items()
+    )
+    return f"<table class='kv'>{rows}</table>"
+
+
+def render_value(v):
+    if isinstance(v, dict):
+        return kv_table(v)
+    if isinstance(v, list):
+        if not v:
+            return "<em>—</em>"
+        if all(isinstance(x, (str, int, float, bool)) for x in v):
+            return "<ul>" + "".join(f"<li>{esc(x)}</li>" for x in v) + "</ul>"
+        if all(isinstance(x, dict) for x in v):
+            keys = []
+            for d in v:
+                for k in d.keys():
+                    if k not in keys:
+                        keys.append(k)
+            head = "".join(f"<th>{esc(k)}</th>" for k in keys)
+            body = ""
+            for d in v:
+                body += "<tr>" + "".join(
+                    f"<td>{render_value(d.get(k, ''))}</td>" for k in keys
+                ) + "</tr>"
+            return (
+                f"<table class='grid'><thead><tr>{head}</tr></thead>"
+                f"<tbody>{body}</tbody></table>"
+            )
+        return "<ul>" + "".join(f"<li>{render_value(x)}</li>" for x in v) + "</ul>"
+    return esc(v)
+
+
+def render_section(sec):
+    sid = sec.get("id", "")
+    title = sec.get("title", "")
+    html = [f"<div class='section' id='{esc(sid)}'>"]
+    html.append(f"<h3>{esc(sid)} · {esc(title)}</h3>")
+    for key, val in sec.items():
+        if key in ("id", "title"):
+            continue
+        html.append(
+            f"<div class='sub'><h4>{esc(key)}</h4>{render_value(val)}</div>"
+        )
+    html.append("</div>")
+    return "\n".join(html)
+
+
+def render_module(mod):
+    mid = mod.get("id", "")
+    title = mod.get("title", "")
+    summary = mod.get("summary", "")
+    sections = mod.get("sections", []) or []
+    html = [f"<section class='module' id='{esc(mid)}'>"]
+    html.append(f"<h2>{esc(mid)} · {esc(title)}</h2>")
+    if summary:
+        html.append(f"<p class='summary'>{esc(summary)}</p>")
+    for sec in sections:
+        html.append(render_section(sec))
+    html.append("</section>")
+    return "\n".join(html)
+
+
+def render_code_example(name, code_obj):
+    if isinstance(code_obj, dict):
+        lang = code_obj.get("language", "")
+        purpose = code_obj.get("purpose", "")
+        body = code_obj.get("code", "")
+        meta_line = (
+            f"<div class='code-meta'><span class='lang'>{esc(lang)}</span> · "
+            f"<span class='purpose'>{esc(purpose)}</span></div>"
+        )
+        return (
+            f"<details><summary>{esc(name)}</summary>"
+            f"{meta_line}<pre><code>{esc(body)}</code></pre></details>"
+        )
+    return (
+        f"<details><summary>{esc(name)}</summary>"
+        f"<pre><code>{esc(code_obj)}</code></pre></details>"
+    )
+
+
+def main():
+    data = json.loads(SRC.read_text(encoding="utf-8"))
+    meta = data["meta"]
+    exec_sum = data["executiveSummary"]
+
+    modules = [data[k] for k in MODULE_ORDER if k in data]
+
+    toc_items = "".join(
+        f"<li><a href='#{esc(m['id'])}'>"
+        f"{esc(m['id'])} · {esc(m['title'].split('—')[-1].strip()[:48])}"
+        f"</a></li>"
+        for m in modules
+    )
+    toc_items += (
+        "<li><a href='#schemas'>Schemas</a></li>"
+        "<li><a href='#code-examples'>Code Examples</a></li>"
+        "<li><a href='#case-studies'>Case Studies</a></li>"
+        "<li><a href='#regulatory'>Regulatory Alignment</a></li>"
+        "<li><a href='#api'>API Endpoints</a></li>"
+    )
+
+    modules_html = "\n".join(render_module(m) for m in modules)
+
+    schemas_html = ""
+    for name, sch in data.get("schemas", {}).items():
+        schemas_html += (
+            f"<details><summary>{esc(name)}</summary>"
+            f"<pre><code>{esc(json.dumps(sch, indent=2))}</code></pre></details>"
+        )
+
+    code_html = ""
+    for name, code in data.get("codeExamples", {}).items():
+        code_html += render_code_example(name, code)
+
+    cs_html = ""
+    for cs in data.get("caseStudies", []):
+        outcomes = cs.get("outcomes", {})
+        outcomes_html = (
+            kv_table(outcomes) if isinstance(outcomes, dict)
+            else render_value(outcomes)
+        )
+        cs_html += (
+            f"<div class='case'><h3>{esc(cs.get('id',''))} · {esc(cs.get('title',''))}</h3>"
+            f"<p><strong>Sector:</strong> {esc(cs.get('sector',''))}</p>"
+            f"<p>{esc(cs.get('summary',''))}</p>"
+            f"<div class='sub'><h4>Outcomes</h4>{outcomes_html}</div>"
+            "</div>"
+        )
+
+    reg = meta.get("regulatoryAlignment", [])
+    reg_html = (
+        "<ul>" + "".join(f"<li>{esc(r)}</li>" for r in reg) + "</ul>"
+        if isinstance(reg, list) else esc(reg)
+    )
+
+    audience = meta.get("audience", [])
+    audience_html = (
+        "<ul>" + "".join(f"<li>{esc(a)}</li>" for a in audience) + "</ul>"
+        if isinstance(audience, list) else esc(audience)
+    )
+
+    subject = meta.get("subjectSystem", {})
+    subject_html = kv_table(subject) if isinstance(subject, dict) else esc(subject)
+
+    inv = meta.get("deliverableInventory", {})
+    inv_html = kv_table(inv) if isinstance(inv, dict) else esc(inv)
+
+    api = data.get("apiEndpoints", {"prefix": "/api/gsifi-aims", "routes": []})
+    api_items = "".join(
+        f"<li><code>{esc(api['prefix'])}{esc(r)}</code></li>"
+        for r in api.get("routes", [])
+    )
+
+    n_modules = len(modules)
+    total_sections = sum(len(m.get("sections", []) or []) for m in modules)
+    n_schemas = len(data.get("schemas", {}))
+    n_code = len(data.get("codeExamples", {}))
+    n_cs = len(data.get("caseStudies", []))
+    n_routes = len(api.get("routes", []))
+    n_overlays = len(
+        data.get("M3_regulatoryOverlays", {})
+            .get("sections", [{}])[0]
+            .get("overlays", [])
+    )
+    n_rsp_versions = len(
+        data.get("M4_rsp", {})
+            .get("sections", [{}])[0]
+            .get("versions", [])
+    )
+    n_phases = len(
+        data.get("M10_roadmap", {})
+            .get("sections", [{}])[0]
+            .get("phases", [])
+    )
+    n_kpis = len(
+        data.get("M10_roadmap", {})
+            .get("sections", [{}, {}])[1]
+            .get("kpis", [])
+    )
+
+    page = f"""<!doctype html>
+<html lang="en">
+<head>
+<meta charset="utf-8" />
+<meta name="viewport" content="width=device-width,initial-scale=1" />
+<title>{esc(meta.get('docRef',''))} — {esc(meta.get('title',''))}</title>
+<meta name="description" content="{esc(meta.get('subtitle',''))}" />
+<style>
+  :root {{
+    --bg:#06101f; --panel:#0d1838; --panel2:#10204a; --fg:#eaf0fb; --muted:#8aa0c2;
+    --accent:#7cc6ff; --accent2:#b693ff; --accent3:#ff9ec7; --line:#1d2a52;
+    --ok:#58f0a7; --warn:#ffcb6b; --crit:#ff7a7a;
+  }}
+  * {{ box-sizing:border-box; }}
+  body {{ margin:0; background:var(--bg); color:var(--fg);
+         font:14px/1.55 -apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,Inter,sans-serif; }}
+  header.hero {{ padding:34px 38px;
+                 background:linear-gradient(135deg,#142563,#0a1438 55%,#06101f);
+                 border-bottom:1px solid var(--line); }}
+  header.hero .doc-ref {{ color:var(--accent3); font-size:12px; letter-spacing:1px;
+                           text-transform:uppercase; margin-bottom:6px; }}
+  header.hero h1 {{ margin:0 0 10px; font-size:25px; letter-spacing:.2px; }}
+  header.hero .subtitle {{ color:var(--muted); max-width:1100px; }}
+  header.hero .badges {{ margin-top:16px; display:flex; gap:8px; flex-wrap:wrap; }}
+  header.hero .badge {{ background:#19255a; color:var(--accent); padding:5px 12px;
+                       border-radius:999px; font-size:12px; border:1px solid var(--line); }}
+  header.hero .badge.warn {{ color:var(--warn); border-color:#5a3f1a; background:#2a1f0d; }}
+  header.hero .badge.ok {{ color:var(--ok); border-color:#1a4a31; background:#0c2a1c; }}
+  header.hero .badge.crit {{ color:var(--crit); border-color:#5a1a1a; background:#2a0d0d; }}
+  header.hero .kpis {{ margin-top:18px; display:flex; gap:18px; flex-wrap:wrap; }}
+  header.hero .kpi {{ background:#0d1532; border:1px solid var(--line); border-radius:10px;
+                      padding:10px 14px; min-width:130px; }}
+  header.hero .kpi .v {{ font-size:20px; color:var(--accent2); font-weight:600; }}
+  header.hero .kpi .l {{ font-size:11px; color:var(--muted); text-transform:uppercase;
+                          letter-spacing:.6px; }}
+  nav.toc {{ position:sticky; top:0; background:#06101fee; backdrop-filter:blur(8px);
+             border-bottom:1px solid var(--line); padding:10px 20px; z-index:5; }}
+  nav.toc ul {{ list-style:none; margin:0; padding:0; display:flex; flex-wrap:wrap; gap:6px; }}
+  nav.toc li a {{ color:var(--accent); text-decoration:none; padding:4px 10px;
+                  border:1px solid var(--line); border-radius:6px; font-size:12px; }}
+  nav.toc li a:hover {{ background:#141e44; }}
+  main {{ padding:24px 36px 80px; max-width:1340px; }}
+  section.module {{ background:var(--panel); border:1px solid var(--line);
+                    border-radius:12px; padding:22px 24px; margin:20px 0; }}
+  section.module h2 {{ margin:0 0 8px; color:var(--accent2); font-size:18px; }}
+  section.module .summary {{ color:var(--muted); margin:0 0 16px; }}
+  .section {{ border-top:1px dashed var(--line); padding-top:14px; margin-top:14px; }}
+  .section h3 {{ margin:0 0 8px; font-size:15px; color:var(--accent); }}
+  .section .sub {{ margin:10px 0; }}
+  .section .sub h4 {{ margin:0 0 6px; font-size:12px; color:var(--muted);
+                      text-transform:uppercase; letter-spacing:.5px; }}
+  table.kv, table.grid {{ width:100%; border-collapse:collapse; font-size:13px;
+                          background:#0d1532; border:1px solid var(--line);
+                          border-radius:6px; overflow:hidden; }}
+  table.kv td, table.grid td, table.grid th {{ padding:6px 10px;
+                                              border-bottom:1px solid var(--line);
+                                              vertical-align:top; text-align:left; }}
+  table.kv td.k {{ color:var(--muted); width:30%; white-space:nowrap; }}
+  table.grid th {{ background:#162248; color:var(--accent); font-weight:600; }}
+  ul {{ margin:6px 0 6px 20px; padding:0; }}
+  code {{ background:#0d1532; padding:1px 5px; border-radius:4px; color:var(--accent); }}
+  pre {{ background:#0d1532; padding:12px; border-radius:6px; overflow:auto;
+         border:1px solid var(--line); font-size:12px; }}
+  details {{ background:#0d1532; border:1px solid var(--line); border-radius:6px;
+             padding:8px 12px; margin:8px 0; }}
+  details summary {{ cursor:pointer; color:var(--accent); }}
+  .code-meta {{ font-size:11px; color:var(--muted); margin:6px 0; }}
+  .code-meta .lang {{ background:#162248; color:var(--accent2); padding:1px 6px;
+                      border-radius:4px; }}
+  .case {{ border-top:1px dashed var(--line); padding-top:14px; margin-top:14px; }}
+  .case h3 {{ margin:0 0 8px; color:var(--accent3); font-size:15px; }}
+  footer {{ color:var(--muted); border-top:1px solid var(--line);
+            padding:16px 36px; font-size:12px; }}
+</style>
+</head>
+<body>
+<header class="hero">
+  <div class="doc-ref">{esc(meta.get('docRef',''))} · {esc(meta.get('classification',''))}</div>
+  <h1>{esc(meta.get('title',''))}</h1>
+  <p class="subtitle">{esc(meta.get('subtitle',''))}</p>
+  <div class="badges">
+    <span class="badge">Version {esc(meta.get('version',''))}</span>
+    <span class="badge">Date {esc(meta.get('date',''))}</span>
+    <span class="badge">Horizon {esc(meta.get('horizon',''))}</span>
+    <span class="badge ok">ISO/IEC 42001 AIMS</span>
+    <span class="badge warn">EU AI Act Annex III §5(b)</span>
+    <span class="badge warn">GDPR Art. 22</span>
+    <span class="badge">SR 11-7 / OCC 2011-12</span>
+    <span class="badge">PRA SS1/23</span>
+    <span class="badge">ECB SSM</span>
+    <span class="badge crit">FCRA / ECOA</span>
+    <span class="badge ok">RSP v2.6 ready</span>
+  </div>
+  <div class="kpis">
+    <div class="kpi"><div class="v">{n_modules}</div><div class="l">Modules</div></div>
+    <div class="kpi"><div class="v">{total_sections}</div><div class="l">Sections</div></div>
+    <div class="kpi"><div class="v">5</div><div class="l">AIMS Sections (1–5)</div></div>
+    <div class="kpi"><div class="v">4</div><div class="l">Annexes (J1–J4)</div></div>
+    <div class="kpi"><div class="v">{n_overlays}</div><div class="l">Regulatory Overlays</div></div>
+    <div class="kpi"><div class="v">{n_rsp_versions}</div><div class="l">RSP Versions</div></div>
+    <div class="kpi"><div class="v">{n_phases}</div><div class="l">Phases</div></div>
+    <div class="kpi"><div class="v">{n_kpis}</div><div class="l">KPIs</div></div>
+    <div class="kpi"><div class="v">{n_schemas}</div><div class="l">Schemas</div></div>
+    <div class="kpi"><div class="v">{n_code}</div><div class="l">Code Examples</div></div>
+    <div class="kpi"><div class="v">{n_cs}</div><div class="l">Case Studies</div></div>
+    <div class="kpi"><div class="v">{n_routes}</div><div class="l">API Routes</div></div>
+  </div>
+</header>
+<nav class="toc"><ul>{toc_items}</ul></nav>
+<main>
+  <section class="module" id="exec">
+    <h2>Executive Summary</h2>
+    {kv_table(exec_sum)}
+  </section>
+
+  <section class="module" id="meta">
+    <h2>Document Metadata</h2>
+    {kv_table({k: v for k, v in meta.items()
+               if k not in ('audience', 'regulatoryAlignment',
+                            'subjectSystem', 'deliverableInventory')})}
+    <div class="section" id="audience">
+      <h3>Audience</h3>
+      {audience_html}
+    </div>
+    <div class="section" id="subject-system">
+      <h3>Subject System</h3>
+      {subject_html}
+    </div>
+    <div class="section" id="inventory">
+      <h3>Deliverable Inventory</h3>
+      {inv_html}
+    </div>
+  </section>
+
+  {modules_html}
+
+  <section class="module" id="regulatory">
+    <h2>Regulatory Alignment</h2>
+    {reg_html}
+  </section>
+
+  <section class="module" id="schemas">
+    <h2>JSON Schemas</h2>
+    <p class="summary">{n_schemas} schemas: AI System Inventory, RSP Manifest, Decision Envelope, Control Mapping, FRIA, Incident Record, FedReg Message, Obligation Spec.</p>
+    {schemas_html}
+  </section>
+
+  <section class="module" id="code-examples">
+    <h2>Code Examples</h2>
+    <p class="summary">{n_code} reference implementations: OPA RSP gate, Terraform WORM evidence, decision envelope signer (Ed25519 + PQC), fairness monitor, FedReg client, predictive drift forecaster, TLA+ obligation spec, Lean FCRA spec, self-healing playbook engine, FastAPI traceability API, Merkle anchor.</p>
+    {code_html}
+  </section>
+
+  <section class="module" id="case-studies">
+    <h2>Case Studies</h2>
+    <p class="summary">{n_cs} reference deployments: EU G-SIB dual ISO/EU AI Act certification, US BHC federated SR 11-7+EU AI Act, UK PRA SS1/23 SMF24 attestation, joint ECB+Fed+PRA examination, self-healing bias drift auto-rollback.</p>
+    {cs_html}
+  </section>
+
+  <section class="module" id="api">
+    <h2>API Endpoints</h2>
+    <p class="summary">Prefix: <code>{esc(api.get('prefix',''))}</code> · Total planned: {n_routes}</p>
+    <ul>{api_items}</ul>
+  </section>
+</main>
+<footer>
+  © {esc(meta.get('docRef',''))} v{esc(meta.get('version',''))} ·
+  {esc(meta.get('date',''))} · {esc(meta.get('classification',''))} ·
+  Owner: {esc(meta.get('owner',''))}
+</footer>
+</body>
+</html>
+"""
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    OUT.write_text(page, encoding="utf-8")
+    size_kb = OUT.stat().st_size // 1024
+    print(f"Wrote {OUT} ({size_kb} KB)")
+    print(f"Modules: {n_modules} | Sections: {total_sections} | "
+          f"Schemas: {n_schemas} | Code: {n_code} | Cases: {n_cs} | Routes: {n_routes}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/rag-agentic-dashboard/gen-gsifi-aims-blueprint.py b/rag-agentic-dashboard/gen-gsifi-aims-blueprint.py
new file mode 100644
index 0000000..9f4a563
--- /dev/null
+++ b/rag-agentic-dashboard/gen-gsifi-aims-blueprint.py
@@ -0,0 +1,1716 @@
+#!/usr/bin/env python3
+"""
+GSIFI-AIMS-BLUEPRINT-WP-037 — Regulator-Grade AI Governance & ISO/IEC 42001
+AIMS Master Blueprint for G-SIFIs (2026-2030)
+
+Generates: data/gsifi-aims-blueprint.json
+
+Coverage:
+  - AI Management System (AIMS) documentation Sections 1-5 + Annexes J1-J4
+  - Multi-jurisdiction regulatory overlays (ECB SSM, Fed SR 11-7, PRA SS1/23,
+    EU AI Act, GDPR)
+  - Regulator Submission Packs (RSP v1.0 -> v2.6) with decision-traceability APIs
+  - Terraform / OPA technical enforcement
+  - Adversarial governance loops + self-healing controls
+  - Predictive governance + formally-verified machine-checkable legal logic
+  - Cross-regulator federation + autonomous supervisory ecosystems
+  - Best-practice patterns for high-risk credit underwriting (2026-2030)
+"""
+
+import json
+from pathlib import Path
+
+HERE = Path(__file__).parent
+OUT = HERE / "data" / "gsifi-aims-blueprint.json"
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# META
+# ──────────────────────────────────────────────────────────────────────────────
+def meta():
+    return {
+        "docRef": "GSIFI-AIMS-BLUEPRINT-WP-037",
+        "version": "1.0.0",
+        "date": "2026-04-30",
+        "title": (
+            "Regulator-Grade AI Governance & ISO/IEC 42001 AIMS Master "
+            "Blueprint for G-SIFIs (2026-2030)"
+        ),
+        "subtitle": (
+            "Design and implementation roadmap for ISO/IEC 42001-aligned AI "
+            "Management Systems, multi-jurisdiction regulatory overlays, "
+            "Regulator Submission Packs (RSP v1.0-v2.6), Terraform/OPA "
+            "technical enforcement, adversarial and self-healing governance "
+            "loops, predictive governance with formally-verified legal logic, "
+            "cross-regulator federation, and autonomous supervisory "
+            "ecosystems for high-risk credit underwriting."
+        ),
+        "classification": (
+            "CONFIDENTIAL — Board / Prudential Regulator / Group Risk / "
+            "Internal Audit / Chief Legal & Compliance Officer"
+        ),
+        "owner": (
+            "Group CRO + Chief AI Officer (CAIO) — co-signed by CCO, GC, "
+            "CISO, DPO, Head of Internal Audit"
+        ),
+        "audience": [
+            "Board of Directors / Risk Committee / Audit Committee",
+            "Executive Committee (CEO, CFO, CRO, CCO, CISO, CAIO, CTO)",
+            "Group Compliance, Legal & Privacy Office",
+            "Internal Audit (3rd Line of Defense)",
+            "Model Risk Management (MRM, 2nd Line of Defense)",
+            "Prudential supervisors (ECB SSM JST, Federal Reserve, PRA, OCC)",
+            "Conduct supervisors (FCA, BaFin, AMF, CFPB)",
+            "Data protection authorities (EDPB, ICO)",
+            "AI safety / standards bodies (AISI, ISO/IEC JTC1 SC42)",
+        ],
+        "horizon": "2026-2030",
+        "outlookHorizon": "2030-2035 (autonomous supervisory ecosystems)",
+        "subjectSystem": {
+            "institutionType": "G-SIFI / G-SIB (FSB list, Bucket 1-4)",
+            "scopeOfAi": (
+                "All AI systems materially impacting capital, liquidity, "
+                "credit, market conduct, AML, fraud, and customer outcomes"
+            ),
+            "anchorUseCase": (
+                "AI-CR-UNDERWRITE-01 — High-risk retail & SME credit "
+                "underwriting (EU AI Act Annex III §5(b) — high-risk)"
+            ),
+            "scale": "20+ jurisdictions · 1,200+ AI systems · 350+ models in production",
+        },
+        "regulatoryAlignment": [
+            "ISO/IEC 42001:2023 — AI Management System (AIMS) — primary anchor",
+            "ISO/IEC 23894:2023 — AI Risk Management",
+            "ISO/IEC 5338:2023 — AI System Life Cycle Processes",
+            "ISO/IEC 27001:2022 / 27701:2019 / 27018:2019",
+            "ISO/IEC TR 24028 / 24029 / 24368 (trustworthiness)",
+            "EU AI Act (Reg. (EU) 2024/1689) — Art. 6, 9, 10, 12, 13, 14, 15, 17, "
+            "26, 27, 49, 53, 55, 72, 73; Annex III §5(b)",
+            "GDPR (Reg. (EU) 2016/679) — Art. 5, 6, 9, 22, 25, 32, 33, 34, 35",
+            "ECB SSM Guide on internal models (2024) + Targeted Review of "
+            "Internal Models (TRIM) AI extensions",
+            "Federal Reserve SR 11-7 / OCC 2011-12 — Model Risk Management",
+            "PRA SS1/23 — Model Risk Management Principles for Banks (UK)",
+            "PRA SS2/21 — Outsourcing & third-party risk management",
+            "FCA Consumer Duty (PS22/9) + AI/ML discussion paper DP5/22",
+            "Basel III/IV — CRR3 / CRD6 — ICAAP Pillar 2 AI add-on",
+            "FCRA (US) §604/§615 + ECOA / Reg B §1002 (adverse action)",
+            "CFPB Circular 2023-03 (algorithmic adverse-action notices)",
+            "NIST AI RMF 1.0 + GenAI Profile (AI 600-1)",
+            "OECD AI Principles + G7 Hiroshima AI Process Code of Conduct",
+            "Council of Europe Framework Convention on AI (2024)",
+            "OWASP LLM Top 10 (2025) / MITRE ATLAS",
+            "SLSA L3 + Sigstore/Cosign + in-toto attestations",
+        ],
+        "deliverableInventory": {
+            "modules": 12,
+            "aimsSections": 5,
+            "annexes": 4,
+            "regulatoryOverlays": 5,
+            "rspVersions": 7,  # v1.0, v1.5, v2.0, v2.2, v2.4, v2.5, v2.6
+            "schemas": 8,
+            "codeExamples": 11,
+            "caseStudies": 5,
+            "phases": 5,
+            "kpis": 16,
+            "controls": 280,
+        },
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# EXECUTIVE SUMMARY
+# ──────────────────────────────────────────────────────────────────────────────
+def executive_summary():
+    return {
+        "purpose": (
+            "Provide G-SIFI boards, regulators, and supervisors a "
+            "regulator-grade, ISO/IEC 42001-anchored master blueprint that "
+            "operationalises AI governance across all jurisdictions in which "
+            "the institution operates, with machine-checkable legal logic "
+            "and autonomous supervisory federation by 2030."
+        ),
+        "scope": (
+            "End-to-end design, implementation, and continuous-supervision "
+            "framework for an AI Management System (AIMS) covering all "
+            "material AI systems — anchored on the AI-CR-UNDERWRITE-01 "
+            "high-risk credit use case."
+        ),
+        "designPrinciples": [
+            "ISO/IEC 42001 as the operating standard, regulator overlays as policy bundles",
+            "Compliance-as-code: every control has Terraform + OPA enforcement",
+            "Decision-traceability: every model decision is reproducible from a signed envelope",
+            "Self-healing governance: detect-then-remediate loops with cryptographic evidence",
+            "Predictive governance: forecast control breaches before they occur",
+            "Formally-verified legal logic: TLA+/Lean specs of obligations",
+            "Federation by default: cross-regulator API with consented disclosure",
+            "Adversarial assurance: continuous red-teaming of both models and controls",
+        ],
+        "headlineKpis": {
+            "timeToRegulatorApprovedDeployment": "<= 14 days (RSP v2.4+)",
+            "rspGenerationLatency": "<= 30 minutes (auto-assembled, signed)",
+            "decisionTraceabilityCoverage": ">= 99.95% of AI decisions",
+            "controlAutomationRate": ">= 95% (Terraform + OPA enforced)",
+            "evidenceAutomation": ">= 96% (no human evidence collection for L1/L2 controls)",
+            "fairnessAirFloor": ">= 0.85 (FCRA / ECOA / EU AI Act Art. 10)",
+            "explainabilityCoverage": "100% of high-risk decisions have SHAP + counterfactual",
+            "adverseActionNoticeSla": "<= 30 days (FCRA §615) — automated for 100% cases",
+            "incidentNotifSlaRegulator": "<= 24h (EU AI Act Art. 73) / 72h (GDPR Art. 33)",
+            "modelInventoryCoverage": "100% — no shadow AI tolerance",
+            "policyDriftMtta": "<= 5 minutes (Terraform plan diff)",
+            "autonomousSupervisorReadiness": "Tier-3 by 2030 (machine-readable filings)",
+            "boardAttestationCadence": "Quarterly + ad-hoc on Sev-1",
+            "auditFindingCloseRate": ">= 95% within SLA",
+            "wormRetention": "10 years (extends SR 11-7 / SEC 17a-4(f) baseline)",
+            "crossRegulatorFederationCount": ">= 8 supervisors integrated",
+        },
+        "boardNarrative": (
+            "This blueprint converts AI governance from a periodic compliance "
+            "exercise into a continuously-attested, regulator-federated "
+            "operating discipline — measurable, monitorable, and provably "
+            "correct against the EU AI Act, ISO/IEC 42001, ECB, Fed, PRA, "
+            "and GDPR by design."
+        ),
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M1 — AIMS Sections 1–5 (ISO/IEC 42001)
+# ──────────────────────────────────────────────────────────────────────────────
+def m1_aims_sections():
+    return {
+        "id": "M1",
+        "title": "M1 — ISO/IEC 42001 AIMS Documentation (Sections 1–5)",
+        "summary": (
+            "Master AIMS documentation set anchored on ISO/IEC 42001:2023 "
+            "clauses 4–10, broken into Sections 1–5 with audit-grade detail."
+        ),
+        "sections": [
+            {
+                "id": "M1-S1",
+                "title": "Section 1 — Context of the Organization (Cl. 4)",
+                "iso42001Clauses": ["4.1", "4.2", "4.3", "4.4"],
+                "deliverables": [
+                    "Internal/external issues register (PEST + tech + regulatory)",
+                    "Interested parties matrix (regulators, customers, employees, society)",
+                    "AIMS scope statement (geographies, business units, AI systems)",
+                    "AI System Inventory v1 (1,200+ systems, classification)",
+                    "Boundary diagram showing AIMS interfaces with EMS/ISMS/QMS",
+                ],
+                "evidenceRefs": ["EVD-AIMS-S1-CTX-2026Q2", "EVD-AIMS-S1-INV-2026Q2"],
+            },
+            {
+                "id": "M1-S2",
+                "title": "Section 2 — Leadership & Policy (Cl. 5)",
+                "iso42001Clauses": ["5.1", "5.2", "5.3"],
+                "deliverables": [
+                    "Board-approved AI Policy (signed by Chair + CEO)",
+                    "AI Roles & Responsibilities matrix (RACI: Board, CAIO, CRO, CCO, DPO)",
+                    "Authority delegation: model approval thresholds by Tier T0–T5",
+                    "Conflict-of-interest controls between 1st/2nd/3rd LoD",
+                ],
+                "evidenceRefs": ["EVD-AIMS-S2-POL-2026Q2", "EVD-AIMS-S2-RACI-2026Q2"],
+            },
+            {
+                "id": "M1-S3",
+                "title": "Section 3 — Planning (Cl. 6)",
+                "iso42001Clauses": ["6.1", "6.2", "6.3"],
+                "deliverables": [
+                    "AI Risks & Opportunities register (linked to ISO 23894 taxonomy)",
+                    "AI Objectives (16 KPIs, board-tracked)",
+                    "Change planning protocol (model promotion gates G0–G5)",
+                    "Statement of Applicability (SoA) covering Annex A + regulator overlays",
+                ],
+                "evidenceRefs": ["EVD-AIMS-S3-RISK-2026Q2", "EVD-AIMS-S3-SOA-2026Q2"],
+            },
+            {
+                "id": "M1-S4",
+                "title": "Section 4 — Support (Cl. 7)",
+                "iso42001Clauses": ["7.1", "7.2", "7.3", "7.4", "7.5"],
+                "deliverables": [
+                    "Resourcing plan (FTEs, GPU compute, evidence storage)",
+                    "Competence framework (CAIO certification, MRM accreditation)",
+                    "Awareness program (annual mandatory training, red-team exercises)",
+                    "Communication plan (internal + regulator + customer)",
+                    "Documented information control (versioning, WORM, retention)",
+                ],
+                "evidenceRefs": ["EVD-AIMS-S4-COMP-2026Q2", "EVD-AIMS-S4-DOC-2026Q2"],
+            },
+            {
+                "id": "M1-S5",
+                "title": "Section 5 — Operation, Performance, Improvement (Cl. 8–10)",
+                "iso42001Clauses": ["8.1", "8.2", "8.3", "9.1", "9.2", "9.3", "10.1", "10.2"],
+                "deliverables": [
+                    "Operational planning & control (life-cycle SOPs per ISO 5338)",
+                    "AI impact assessment process (GDPR DPIA + EU AI Act FRIA)",
+                    "Performance evaluation (KPI dashboard, internal audit plan)",
+                    "Management review minutes (quarterly, board-attested)",
+                    "Continual improvement loop (CAPA register, RCA)",
+                ],
+                "evidenceRefs": [
+                    "EVD-AIMS-S5-OPS-2026Q2",
+                    "EVD-AIMS-S5-MR-2026Q2",
+                    "EVD-AIMS-S5-CAPA-2026Q2",
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M2 — AIMS Annexes J1–J4
+# ──────────────────────────────────────────────────────────────────────────────
+def m2_aims_annexes():
+    return {
+        "id": "M2",
+        "title": "M2 — AIMS Annexes J1–J4 (Implementation Detail)",
+        "summary": (
+            "Four institution-specific annexes extending ISO/IEC 42001 "
+            "Annex A/B with G-SIFI-grade depth."
+        ),
+        "sections": [
+            {
+                "id": "M2-S1",
+                "title": "Annex J1 — AI System Inventory & Classification",
+                "content": (
+                    "Authoritative register of all AI systems with EU AI Act "
+                    "tiering (Prohibited / High-Risk / Limited / Minimal), "
+                    "internal capability tier T0–T5, owning business unit, "
+                    "data classification, model risk tier, and impact zones."
+                ),
+                "fields": [
+                    "systemId",
+                    "businessOwner",
+                    "euAiActTier",
+                    "internalTier",
+                    "modelRiskTier",
+                    "annexIIIRef",
+                    "lastFRIA",
+                    "lastDPIA",
+                    "rspVersion",
+                    "regulatorEngagementStatus",
+                ],
+            },
+            {
+                "id": "M2-S2",
+                "title": "Annex J2 — Statement of Applicability (SoA) + Control Mapping",
+                "content": (
+                    "Mapping of ISO/IEC 42001 Annex A controls + 280 "
+                    "institution-specific controls to regulator overlays "
+                    "(ECB, Fed, PRA, EU AI Act, GDPR), each with a "
+                    "Terraform/OPA enforcement reference and an evidence "
+                    "automation status."
+                ),
+                "controlCategories": [
+                    "AC — Accountability",
+                    "RM — Risk Management",
+                    "DG — Data Governance",
+                    "MD — Model Development",
+                    "VV — Validation & Verification",
+                    "DP — Deployment",
+                    "MO — Monitoring",
+                    "IR — Incident Response",
+                    "TP — Third-Party",
+                    "TR — Transparency",
+                ],
+                "totalControls": 280,
+            },
+            {
+                "id": "M2-S3",
+                "title": "Annex J3 — AI Impact Assessment (FRIA + DPIA Combined)",
+                "content": (
+                    "Unified template combining EU AI Act Fundamental "
+                    "Rights Impact Assessment (Art. 27) with GDPR DPIA "
+                    "(Art. 35) and SR 11-7 model materiality assessment."
+                ),
+                "phases": [
+                    "Phase A — Purpose & Necessity",
+                    "Phase B — Risk Identification (12 axes)",
+                    "Phase C — Risk Evaluation (likelihood × severity × scope)",
+                    "Phase D — Mitigation Plan",
+                    "Phase E — Residual Risk Acceptance (CRO sign-off)",
+                    "Phase F — Monitoring & Review (auto-rerun on drift)",
+                ],
+            },
+            {
+                "id": "M2-S4",
+                "title": "Annex J4 — Regulator Submission Pack (RSP) Template",
+                "content": (
+                    "Master template that produces RSP v1.0–v2.6 with "
+                    "decision-traceability links, model cards, eval results, "
+                    "monitoring telemetry, and signed attestations."
+                ),
+                "rspContents": [
+                    "Cover & Executive Summary",
+                    "Model Card (Mitchell+ format extended)",
+                    "Data Sheet (Gebru+ format extended)",
+                    "FRIA + DPIA",
+                    "Validation Report (independent 2nd LoD sign-off)",
+                    "Monitoring Plan + KPI baseline",
+                    "Incident Response Plan (model-specific)",
+                    "Decision Traceability API endpoint + sample decisions",
+                    "Cryptographic attestation bundle (Sigstore + Rekor)",
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M3 — Multi-Jurisdiction Regulatory Overlays
+# ──────────────────────────────────────────────────────────────────────────────
+def m3_regulatory_overlays():
+    return {
+        "id": "M3",
+        "title": "M3 — Multi-Jurisdiction Regulatory Overlays",
+        "summary": (
+            "Five regulator overlays applied as policy bundles on top of the "
+            "ISO/IEC 42001 baseline."
+        ),
+        "sections": [
+            {
+                "id": "M3-S1",
+                "title": "Overlay catalog",
+                "overlays": [
+                    {
+                        "id": "OVL-ECB",
+                        "name": "ECB SSM Overlay",
+                        "scope": "Significant Institutions under direct ECB supervision",
+                        "keyRefs": [
+                            "ECB Guide to Internal Models (2024)",
+                            "TRIM AI extensions",
+                            "ECB SSM Supervisory Priorities 2025-2027",
+                        ],
+                        "additionalControls": [
+                            "ECB-AI-01 Model change notification within 5 business days",
+                            "ECB-AI-02 JST-accessible model inventory",
+                            "ECB-AI-03 ICAAP Pillar 2 AI capital add-on quantification",
+                        ],
+                    },
+                    {
+                        "id": "OVL-FED",
+                        "name": "Federal Reserve SR 11-7 Overlay",
+                        "scope": "US bank holding companies / FBOs",
+                        "keyRefs": [
+                            "SR 11-7 (2011) + 2021 supplemental guidance",
+                            "OCC 2011-12",
+                            "FDIC FIL-22-2017",
+                            "Joint statement on Risk-Based Approach to Third-Party Risk (2023)",
+                        ],
+                        "additionalControls": [
+                            "FED-AI-01 Independent model validation by qualified 2nd LoD",
+                            "FED-AI-02 Effective challenge documented for every Tier-1 model",
+                            "FED-AI-03 Ongoing monitoring with documented thresholds",
+                        ],
+                    },
+                    {
+                        "id": "OVL-PRA",
+                        "name": "PRA SS1/23 Overlay",
+                        "scope": "UK PRA-authorised firms",
+                        "keyRefs": ["PRA SS1/23", "PRA SS2/21 outsourcing", "FCA Consumer Duty"],
+                        "additionalControls": [
+                            "PRA-AI-01 Model risk tiering with board-approved thresholds",
+                            "PRA-AI-02 Senior Manager (SMF24) accountability for MRM",
+                            "PRA-AI-03 Annual model risk self-assessment to PRA",
+                        ],
+                    },
+                    {
+                        "id": "OVL-EUAIA",
+                        "name": "EU AI Act Overlay",
+                        "scope": "All AI systems placed on the EU market or affecting EU persons",
+                        "keyRefs": [
+                            "Reg. (EU) 2024/1689",
+                            "EU AI Act Annex III §5(b) — credit scoring",
+                            "Commission implementing acts 2025-2026",
+                        ],
+                        "additionalControls": [
+                            "EUAIA-AI-01 CE conformity (Art. 43) for high-risk systems",
+                            "EUAIA-AI-02 Post-market monitoring (Art. 72) live",
+                            "EUAIA-AI-03 Serious incident reporting within 15 days (Art. 73)",
+                            "EUAIA-AI-04 Registration in EU database (Art. 49)",
+                        ],
+                    },
+                    {
+                        "id": "OVL-GDPR",
+                        "name": "GDPR Overlay",
+                        "scope": "Any processing of EU personal data",
+                        "keyRefs": [
+                            "Reg. (EU) 2016/679 Articles 5/6/9/22/25/32/33/34/35",
+                            "EDPB Guidelines 03/2022 on AI",
+                        ],
+                        "additionalControls": [
+                            "GDPR-AI-01 Art. 22 safeguards: human review path documented",
+                            "GDPR-AI-02 DPIA refreshed on material change",
+                            "GDPR-AI-03 Data minimisation tested via leakage probes",
+                        ],
+                    },
+                ],
+            },
+            {
+                "id": "M3-S2",
+                "title": "Overlay precedence & conflict resolution",
+                "rules": [
+                    "Strictest applicable provision wins (tier ordering).",
+                    "Where overlays diverge on disclosure scope, union of "
+                    "disclosures applies; classification follows the home regulator.",
+                    "Conflict log maintained with Legal sign-off for every override.",
+                ],
+            },
+            {
+                "id": "M3-S3",
+                "title": "Mapping matrix snapshot",
+                "matrix": [
+                    {
+                        "control": "Independent validation",
+                        "ISO42001": "8.3",
+                        "ECB": "ECB-AI-01/03",
+                        "Fed": "FED-AI-01/02",
+                        "PRA": "PRA-AI-02",
+                        "EUAIA": "Art. 17 QMS / 43",
+                        "GDPR": "—",
+                    },
+                    {
+                        "control": "Adverse-action explanation",
+                        "ISO42001": "Annex A 6.2.7",
+                        "ECB": "—",
+                        "Fed": "FCRA §615",
+                        "PRA": "FCA Consumer Duty",
+                        "EUAIA": "Art. 13/86",
+                        "GDPR": "Art. 22",
+                    },
+                    {
+                        "control": "Post-market monitoring",
+                        "ISO42001": "9.1",
+                        "ECB": "ECB-AI-02",
+                        "Fed": "FED-AI-03",
+                        "PRA": "PRA-AI-03",
+                        "EUAIA": "Art. 72",
+                        "GDPR": "Art. 35(11)",
+                    },
+                    {
+                        "control": "Incident reporting",
+                        "ISO42001": "10.2",
+                        "ECB": "Operational incident framework",
+                        "Fed": "SR 11-7 weakness reporting",
+                        "PRA": "SS1/23 §3.5",
+                        "EUAIA": "Art. 73",
+                        "GDPR": "Art. 33/34",
+                    },
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M4 — Regulator Submission Packs RSP v1.0 → v2.6
+# ──────────────────────────────────────────────────────────────────────────────
+def m4_rsp():
+    return {
+        "id": "M4",
+        "title": "M4 — Regulator Submission Packs (RSP v1.0 → v2.6)",
+        "summary": (
+            "Versioned submission packs evolving from PDF-based static packs "
+            "to fully machine-readable, signed, decision-traceable bundles."
+        ),
+        "sections": [
+            {
+                "id": "M4-S1",
+                "title": "Version roadmap",
+                "versions": [
+                    {
+                        "id": "RSP-v1.0",
+                        "year": 2026,
+                        "format": "PDF + JSON manifest",
+                        "scope": "Single jurisdiction (home regulator)",
+                        "automation": "30%",
+                        "signing": "PGP detached signature",
+                    },
+                    {
+                        "id": "RSP-v1.5",
+                        "year": 2026,
+                        "format": "PDF + JSON-LD + Sigstore",
+                        "scope": "Home + 1 host regulator",
+                        "automation": "55%",
+                        "signing": "Sigstore + Rekor transparency log",
+                    },
+                    {
+                        "id": "RSP-v2.0",
+                        "year": 2027,
+                        "format": "Structured JSON-LD bundle (machine-readable)",
+                        "scope": "Multi-jurisdiction (ECB + PRA + Fed)",
+                        "automation": "75%",
+                        "signing": "in-toto attestations",
+                    },
+                    {
+                        "id": "RSP-v2.2",
+                        "year": 2027,
+                        "format": "JSON-LD + Decision-Traceability API",
+                        "scope": "Adds GDPR + EU AI Act DB linkage",
+                        "automation": "85%",
+                        "signing": "in-toto + Cosign",
+                    },
+                    {
+                        "id": "RSP-v2.4",
+                        "year": 2028,
+                        "format": "JSON-LD + live API + OPA-validated policy bundle",
+                        "scope": "All overlays, federated submission",
+                        "automation": "92%",
+                        "signing": "PQC-ready (Dilithium hybrid)",
+                    },
+                    {
+                        "id": "RSP-v2.5",
+                        "year": 2029,
+                        "format": "v2.4 + formally-verified obligation graph",
+                        "scope": "Adds machine-checkable legal logic",
+                        "automation": "95%",
+                        "signing": "PQC + Merkle anchored to public ledger",
+                    },
+                    {
+                        "id": "RSP-v2.6",
+                        "year": 2030,
+                        "format": "Continuous streaming attestation",
+                        "scope": "Autonomous-supervisor compatible",
+                        "automation": "98%",
+                        "signing": "PQC + FROST threshold + ZK predicates",
+                    },
+                ],
+            },
+            {
+                "id": "M4-S2",
+                "title": "RSP package structure (v2.4+)",
+                "structure": [
+                    "/rsp/manifest.jsonld — top-level bundle",
+                    "/rsp/model-card.json",
+                    "/rsp/datasheet.json",
+                    "/rsp/fria-dpia.json",
+                    "/rsp/validation-report.json",
+                    "/rsp/monitoring-plan.json",
+                    "/rsp/incident-plan.json",
+                    "/rsp/decisions/ (signed decision envelopes)",
+                    "/rsp/policy-bundle.tar.gz (OPA bundle)",
+                    "/rsp/attestations/ (in-toto / Cosign / Rekor)",
+                    "/rsp/hash-chain.json (Merkle root + signatures)",
+                ],
+            },
+            {
+                "id": "M4-S3",
+                "title": "Decision-traceability API",
+                "endpoints": [
+                    "GET /rsp/{rspId}/decisions/{decisionId} — full reproducible decision",
+                    "GET /rsp/{rspId}/decisions?subjectId=… — subject access",
+                    "GET /rsp/{rspId}/lineage — model + data lineage graph",
+                    "GET /rsp/{rspId}/attestations — verifiable bundle",
+                    "POST /rsp/{rspId}/challenge — supervisor counterfactual probe",
+                ],
+                "slas": {
+                    "decisionLookup": "<= 200 ms p95",
+                    "lineageGraph": "<= 1 s p95",
+                    "challengeReply": "<= 5 minutes p95",
+                },
+                "auth": "mTLS + supervisor SPIFFE ID + per-call OPA policy",
+            },
+            {
+                "id": "M4-S4",
+                "title": "RSP issuance pipeline",
+                "stages": [
+                    "Trigger: model promotion / quarterly cadence / supervisor request",
+                    "Assemble: pull artefacts from registry, evaluator, monitor",
+                    "Validate: OPA policy bundle compliance check",
+                    "Sign: in-toto layout + Cosign + Rekor entry",
+                    "Publish: regulator portal + internal evidence WORM",
+                    "Notify: supervisor + Internal Audit + Board pack",
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M5 — Terraform / OPA technical enforcement
+# ──────────────────────────────────────────────────────────────────────────────
+def m5_technical_enforcement():
+    return {
+        "id": "M5",
+        "title": "M5 — Terraform + OPA Technical Enforcement",
+        "summary": (
+            "Compliance-as-code substrate enforcing AIMS controls at "
+            "infrastructure, pipeline, and runtime layers."
+        ),
+        "sections": [
+            {
+                "id": "M5-S1",
+                "title": "Terraform modules",
+                "modules": [
+                    {"name": "aims-baseline", "purpose": "VPC/KMS/IAM/WORM-S3/Kafka baseline"},
+                    {"name": "aims-evidence", "purpose": "Object Lock + Lambda hash-chain anchor"},
+                    {"name": "aims-runtime", "purpose": "EKS/GKE clusters + admission controllers"},
+                    {"name": "aims-supervisor", "purpose": "Supervisor mTLS endpoints + SPIFFE"},
+                    {"name": "aims-pqc", "purpose": "PQC KMS keys + dual-signing CI"},
+                ],
+            },
+            {
+                "id": "M5-S2",
+                "title": "OPA policy bundles",
+                "bundles": [
+                    "policy/aims-baseline.tar.gz (Annex A controls)",
+                    "policy/overlay-ecb.tar.gz",
+                    "policy/overlay-fed.tar.gz",
+                    "policy/overlay-pra.tar.gz",
+                    "policy/overlay-euaia.tar.gz",
+                    "policy/overlay-gdpr.tar.gz",
+                    "policy/use-case-credit-underwriting.tar.gz",
+                ],
+                "decisionPoints": [
+                    "Terraform plan (pre-apply) — block insecure infra",
+                    "CI gate (pre-merge) — model card + eval coverage",
+                    "Admission controller (Kubernetes) — image attestation",
+                    "Inference gateway (runtime) — per-call obligations",
+                    "Egress filter — prohibited-use checks",
+                ],
+            },
+            {
+                "id": "M5-S3",
+                "title": "Continuous configuration audit",
+                "controls": [
+                    "Daily Terraform drift scan with auto-remediation PR",
+                    "Hourly OPA bundle integrity check (signed digest)",
+                    "Per-region misconfiguration KPI dashboard",
+                    "Auto-quarantine of non-compliant workloads",
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M6 — Adversarial & self-healing governance loops
+# ──────────────────────────────────────────────────────────────────────────────
+def m6_adversarial_self_healing():
+    return {
+        "id": "M6",
+        "title": "M6 — Adversarial & Self-Healing Governance Loops",
+        "summary": (
+            "Continuous adversarial exercise of both models and controls, "
+            "paired with auto-remediation that closes the loop without "
+            "human intervention for known failure modes."
+        ),
+        "sections": [
+            {
+                "id": "M6-S1",
+                "title": "Adversarial governance loop",
+                "stages": [
+                    "Generate: red-team agents author attacks against models + controls",
+                    "Execute: attacks run in sandboxed twin environment",
+                    "Detect: monitors flag deltas vs. baseline behavior",
+                    "Triage: severity scored against impact taxonomy",
+                    "Remediate: control patch / model rollback / policy update",
+                    "Attest: signed evidence captured in WORM",
+                ],
+                "cadence": "Continuous (on-demand + nightly + monthly chaos day)",
+            },
+            {
+                "id": "M6-S2",
+                "title": "Self-healing playbooks",
+                "playbooks": [
+                    {
+                        "id": "SH-01",
+                        "trigger": "PSI > 0.2 on protected attribute",
+                        "action": "Auto-rollback to previous model version + open Sev-2 ticket",
+                        "humanGate": "CRO post-hoc review within 24h",
+                    },
+                    {
+                        "id": "SH-02",
+                        "trigger": "OPA policy bundle digest mismatch",
+                        "action": "Quarantine workload + restore last-known-good bundle",
+                        "humanGate": "CISO + CCO joint review",
+                    },
+                    {
+                        "id": "SH-03",
+                        "trigger": "Adverse-action SLA breach predicted",
+                        "action": "Failover to deterministic fallback scoring + notify ops",
+                        "humanGate": "Head of Credit + DPO",
+                    },
+                    {
+                        "id": "SH-04",
+                        "trigger": "FRIA risk score escalation",
+                        "action": "Block new deployments of system + escalate to Risk Committee",
+                        "humanGate": "Board Risk Committee within 5 business days",
+                    },
+                ],
+            },
+            {
+                "id": "M6-S3",
+                "title": "Adversarial assurance KPIs",
+                "kpis": {
+                    "redTeamCoverage": ">= 95% of high-risk systems / quarter",
+                    "novelAttackDiscoveryRate": ">= 5 net-new attack classes / year",
+                    "selfHealingResolutionRate": ">= 80% Sev-2 without human action",
+                    "meanTimeToRemediate": "<= 30 min (Sev-2), <= 4 h (Sev-1)",
+                },
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M7 — Predictive governance & formally-verified legal logic
+# ──────────────────────────────────────────────────────────────────────────────
+def m7_predictive_formal():
+    return {
+        "id": "M7",
+        "title": "M7 — Predictive Governance & Formally-Verified Legal Logic",
+        "summary": (
+            "Forecast control breaches before they occur and prove "
+            "obligations are correctly implemented using machine-checkable "
+            "specifications."
+        ),
+        "sections": [
+            {
+                "id": "M7-S1",
+                "title": "Predictive governance",
+                "approach": (
+                    "Treat governance KPIs (PSI, AIR, MTTR, evidence "
+                    "completeness) as time series; forecast breach "
+                    "probability and pre-emptively trigger remediation."
+                ),
+                "models": [
+                    "Drift forecaster (Prophet + ARIMA ensemble) — 7-day horizon",
+                    "Fairness drift forecaster — protected-attribute aware",
+                    "Control-fatigue forecaster (audit findings as proxy)",
+                    "Regulatory-question forecaster (LLM-driven, supervised by Legal)",
+                ],
+                "outputs": [
+                    "Predicted breaches with calibrated confidence",
+                    "Recommended interventions (pre-staged remediation PRs)",
+                    "Board pre-warning dashboard (T-30 days)",
+                ],
+            },
+            {
+                "id": "M7-S2",
+                "title": "Formally-verified obligation graph",
+                "approach": (
+                    "Encode regulator obligations as an obligation graph in "
+                    "TLA+/Lean and prove the implementation refines the "
+                    "specification."
+                ),
+                "specs": [
+                    "FCRA §615 adverse-action obligation (Lean spec, mechanically checked)",
+                    "GDPR Art. 22 human-review-path obligation (TLA+)",
+                    "EU AI Act Art. 73 incident-reporting obligation (TLA+ liveness)",
+                    "ECB ICAAP Pillar 2 AI add-on quantification (Lean)",
+                ],
+                "deliverable": (
+                    "Each spec ships with a CI job that fails the build if a "
+                    "code change breaks refinement."
+                ),
+            },
+            {
+                "id": "M7-S3",
+                "title": "Counterfactual + causal regulator queries",
+                "capability": (
+                    "Supervisors can issue causal queries (\"if income were "
+                    "+10%, would the decision flip?\") that the system "
+                    "answers with a causal model + uncertainty, not just "
+                    "correlations."
+                ),
+                "engines": [
+                    "DoWhy + EconML for causal effect estimation",
+                    "DiCE / Alibi for actionable counterfactuals",
+                    "LiNGAM / NOTEARS for structure discovery (governed)",
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M8 — Cross-regulator federation & autonomous supervisory ecosystem
+# ──────────────────────────────────────────────────────────────────────────────
+def m8_federation_supervisory():
+    return {
+        "id": "M8",
+        "title": "M8 — Cross-Regulator Federation & Autonomous Supervisory Ecosystem",
+        "summary": (
+            "Federate disclosures across supervisors and prepare for "
+            "autonomous supervisory ecosystems by 2030."
+        ),
+        "sections": [
+            {
+                "id": "M8-S1",
+                "title": "Federation protocol (FedReg)",
+                "transport": "mTLS + SPIFFE IDs + OAuth2 Mutual-TLS Client Auth",
+                "schema": "JSON-LD with shared regulator vocabulary (W3C ODRL extension)",
+                "operations": [
+                    "Disclose: scoped artefact share with consent metadata",
+                    "Subscribe: supervisor receives delta stream",
+                    "Challenge: supervisor issues counterfactual / explainability query",
+                    "Attest: institution returns signed answer with provenance",
+                ],
+                "consentModel": "Per-scope, per-purpose, time-bounded, revocable",
+            },
+            {
+                "id": "M8-S2",
+                "title": "Autonomous Supervisory Tiers",
+                "tiers": [
+                    {"tier": "T0", "name": "Manual", "year": "<2026", "description": "PDF + portal uploads"},
+                    {"tier": "T1", "name": "Structured", "year": "2026", "description": "Machine-readable RSP, manual review"},
+                    {"tier": "T2", "name": "Streaming", "year": "2027-2028", "description": "Continuous attestation feed"},
+                    {"tier": "T3", "name": "Federated", "year": "2028-2029", "description": "Cross-regulator query graph"},
+                    {"tier": "T4", "name": "Autonomous (advisory)", "year": "2029-2030", "description": "Supervisor AI agents issue advisories"},
+                    {"tier": "T5", "name": "Autonomous (binding-with-human-override)", "year": "2030+", "description": "Binding decisions with statutory human override"},
+                ],
+            },
+            {
+                "id": "M8-S3",
+                "title": "Privacy & sovereignty controls in federation",
+                "controls": [
+                    "Differential privacy on aggregate disclosures (ε <= 1)",
+                    "Zero-knowledge predicates for sensitive thresholds",
+                    "Data residency tags enforced at egress filter",
+                    "Per-jurisdiction key custody with HSM + threshold signing (FROST)",
+                ],
+            },
+            {
+                "id": "M8-S4",
+                "title": "Joint examination workflow",
+                "scenario": (
+                    "ECB + FRB + PRA jointly examine AI-CR-UNDERWRITE-01. "
+                    "Each receives scoped, signed RSP slices; queries "
+                    "federated through FedReg; institution responses "
+                    "attested into a shared transparency log."
+                ),
+                "sla": "Joint final report within 30 calendar days",
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M9 — High-risk credit underwriting use case
+# ──────────────────────────────────────────────────────────────────────────────
+def m9_credit_underwriting():
+    return {
+        "id": "M9",
+        "title": "M9 — High-Risk Credit Underwriting Best-Practice Pattern (AI-CR-UNDERWRITE-01)",
+        "summary": (
+            "Reference end-to-end pattern for high-risk retail & SME credit "
+            "underwriting under EU AI Act Annex III §5(b), FCRA, ECOA, and "
+            "PRA / Fed MRM."
+        ),
+        "sections": [
+            {
+                "id": "M9-S1",
+                "title": "Use-case scope & risk classification",
+                "details": {
+                    "euAiActTier": "High-risk (Annex III §5(b))",
+                    "internalTier": "T3 (material consumer impact)",
+                    "modelRiskTier": "Tier 1",
+                    "regulators": ["ECB", "Fed", "PRA", "FCA", "CFPB", "ICO", "EDPB"],
+                    "decisionVolume": "~12M decisions / year",
+                },
+            },
+            {
+                "id": "M9-S2",
+                "title": "Data governance",
+                "controls": [
+                    "Datasheet (Gebru+) with provenance, sampling, bias notes",
+                    "Protected attributes proxied + monitored (no direct use)",
+                    "Synthetic counterfactual training augmentation for AIR uplift",
+                    "Quarterly representativeness audit by Internal Audit",
+                ],
+            },
+            {
+                "id": "M9-S3",
+                "title": "Model development & validation",
+                "controls": [
+                    "Champion/challenger with at least 2 independent architectures",
+                    "GBM + monotonic constraints on protected proxies",
+                    "Independent 2nd LoD validation (effective challenge)",
+                    "FRIA + DPIA refreshed each retrain",
+                    "Reproducibility: bit-exact training pipeline pinned",
+                ],
+            },
+            {
+                "id": "M9-S4",
+                "title": "Decisioning & adverse action",
+                "controls": [
+                    "Per-decision SHAP + counterfactual stored with envelope",
+                    "Adverse-action notice generated within 24h (FCRA §615)",
+                    "GDPR Art. 22 human-review path for any decision contested",
+                    "EU AI Act Art. 86 right to explanation served via portal",
+                    "Decision envelope signed (Ed25519 + PQC dual-sign)",
+                ],
+            },
+            {
+                "id": "M9-S5",
+                "title": "Monitoring & continuous compliance",
+                "controls": [
+                    "Drift: PSI per feature + per protected attribute, daily",
+                    "Fairness: AIR + EOD + DI ratio, daily",
+                    "Stability: KS, ROC-AUC delta vs. baseline, weekly",
+                    "Calibration: Brier score, monthly",
+                    "Adversarial: prompt-injection / data-poisoning probes, nightly",
+                ],
+            },
+            {
+                "id": "M9-S6",
+                "title": "Regulator engagement",
+                "cadence": [
+                    "Quarterly RSP v2.4 issuance to home + host regulators",
+                    "Material change notification within 5 business days (ECB-AI-01)",
+                    "Annual joint examination drill",
+                    "Live decision-traceability API for supervisor on-demand probes",
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M10 — Implementation roadmap (5 phases)
+# ──────────────────────────────────────────────────────────────────────────────
+def m10_roadmap():
+    return {
+        "id": "M10",
+        "title": "M10 — Implementation Roadmap (2026–2030)",
+        "summary": "Five-phase, board-tracked program plan with gates and KPIs.",
+        "sections": [
+            {
+                "id": "M10-S1",
+                "title": "Phase plan",
+                "phases": [
+                    {
+                        "id": "P1",
+                        "name": "Foundation",
+                        "window": "2026 H1",
+                        "objectives": [
+                            "Adopt ISO/IEC 42001 AIMS Sections 1–5",
+                            "Stand up AI System Inventory (Annex J1)",
+                            "Issue RSP v1.0 for AI-CR-UNDERWRITE-01",
+                            "Launch CAIO office with board mandate",
+                        ],
+                        "exitGate": "Board approval of AIMS + first RSP filed",
+                    },
+                    {
+                        "id": "P2",
+                        "name": "Industrialise",
+                        "window": "2026 H2 – 2027 H1",
+                        "objectives": [
+                            "Deploy Terraform + OPA enforcement substrate",
+                            "Roll out SoA (Annex J2) across 100% Tier-1 systems",
+                            "Issue RSP v1.5 + v2.0",
+                            "Launch adversarial governance loop",
+                        ],
+                        "exitGate": ">= 75% control automation",
+                    },
+                    {
+                        "id": "P3",
+                        "name": "Federate",
+                        "window": "2027 H2 – 2028",
+                        "objectives": [
+                            "RSP v2.2 + v2.4 with multi-regulator scope",
+                            "FedReg federation pilot with ECB + PRA + Fed",
+                            "Activate self-healing playbooks SH-01..04",
+                            "Stand up predictive governance forecasters",
+                        ],
+                        "exitGate": "Joint ECB+Fed+PRA examination drill passed",
+                    },
+                    {
+                        "id": "P4",
+                        "name": "Verify",
+                        "window": "2029",
+                        "objectives": [
+                            "Formally verified obligation graph live for top 5 obligations",
+                            "RSP v2.5 with machine-checkable legal logic",
+                            "Counterfactual / causal supervisor queries supported",
+                            "Autonomous supervisor T2->T3",
+                        ],
+                        "exitGate": "Independent assurance from ISO 42001 certification body",
+                    },
+                    {
+                        "id": "P5",
+                        "name": "Autonomous",
+                        "window": "2030",
+                        "objectives": [
+                            "RSP v2.6 streaming attestation",
+                            "Autonomous supervisor T4 advisory mode active",
+                            "Cross-regulator binding-with-override pilot",
+                            "PQC + ZK predicates fully deployed",
+                        ],
+                        "exitGate": "Autonomous advisory disclosures accepted by 8+ supervisors",
+                    },
+                ],
+            },
+            {
+                "id": "M10-S2",
+                "title": "KPI dashboard",
+                "kpis": [
+                    {"id": "K1", "name": "Time-to-regulator-approved deployment", "target": "<= 14 days"},
+                    {"id": "K2", "name": "RSP generation latency", "target": "<= 30 minutes"},
+                    {"id": "K3", "name": "Decision-traceability coverage", "target": ">= 99.95%"},
+                    {"id": "K4", "name": "Control automation rate", "target": ">= 95%"},
+                    {"id": "K5", "name": "Evidence automation", "target": ">= 96%"},
+                    {"id": "K6", "name": "Fairness AIR floor", "target": ">= 0.85"},
+                    {"id": "K7", "name": "Explainability coverage (high-risk)", "target": "100%"},
+                    {"id": "K8", "name": "Adverse-action SLA", "target": "<= 24h auto"},
+                    {"id": "K9", "name": "Regulator notification SLA", "target": "<= 24h / 72h"},
+                    {"id": "K10", "name": "Model inventory coverage", "target": "100%"},
+                    {"id": "K11", "name": "Policy-drift MTTA", "target": "<= 5 min"},
+                    {"id": "K12", "name": "Self-healing resolution rate", "target": ">= 80% Sev-2"},
+                    {"id": "K13", "name": "Audit finding closure", "target": ">= 95% within SLA"},
+                    {"id": "K14", "name": "Board attestation cadence", "target": "Quarterly + ad-hoc"},
+                    {"id": "K15", "name": "WORM retention", "target": "10 years"},
+                    {"id": "K16", "name": "Federated supervisor count", "target": ">= 8"},
+                ],
+            },
+            {
+                "id": "M10-S3",
+                "title": "Top risks & mitigations",
+                "risks": [
+                    {"id": "R1", "risk": "Regulatory divergence post-2027", "mitigation": "Overlay precedence engine + Legal council monthly"},
+                    {"id": "R2", "risk": "Supervisor reluctance to accept machine-readable filings", "mitigation": "Dual format (PDF + JSON-LD) until T2"},
+                    {"id": "R3", "risk": "Formal verification toolchain immaturity", "mitigation": "Hybrid test-based + spec-based assurance"},
+                    {"id": "R4", "risk": "PQC migration breakage", "mitigation": "Hybrid signing + staged rollouts"},
+                    {"id": "R5", "risk": "Self-healing causes incident drift", "mitigation": "Human gate on every Sev-1; quarterly chaos drills"},
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M11 — Governance operating model (RACI + 3 LoD)
+# ──────────────────────────────────────────────────────────────────────────────
+def m11_operating_model():
+    return {
+        "id": "M11",
+        "title": "M11 — Governance Operating Model (3 LoD + RACI)",
+        "summary": "Roles, accountabilities, and committee architecture.",
+        "sections": [
+            {
+                "id": "M11-S1",
+                "title": "Three Lines of Defense",
+                "lod": [
+                    {"line": "1st LoD", "owner": "Business + AI engineering", "responsibilities": "Build, operate, monitor models within risk appetite"},
+                    {"line": "2nd LoD", "owner": "MRM + Compliance + DPO + CISO", "responsibilities": "Independent challenge, validation, policy, oversight"},
+                    {"line": "3rd LoD", "owner": "Internal Audit", "responsibilities": "Audit AIMS effectiveness; audit the 2nd LoD"},
+                ],
+            },
+            {
+                "id": "M11-S2",
+                "title": "RACI matrix (key activities)",
+                "matrix": [
+                    {"activity": "Approve AI Policy", "Board": "A", "CEO": "R", "CRO": "C", "CCO": "C", "CAIO": "C", "DPO": "I"},
+                    {"activity": "Approve Tier-1 model", "Board": "I", "CEO": "I", "CRO": "A", "CCO": "C", "CAIO": "R", "DPO": "C"},
+                    {"activity": "Issue RSP", "Board": "I", "CEO": "I", "CRO": "A", "CCO": "R", "CAIO": "R", "DPO": "C"},
+                    {"activity": "Sev-1 incident response", "Board": "I", "CEO": "I", "CRO": "A", "CCO": "C", "CAIO": "R", "DPO": "C", "CISO": "R"},
+                    {"activity": "Annual AIMS audit", "Board": "I", "CEO": "I", "CRO": "C", "CCO": "C", "CAIO": "C", "DPO": "C", "InternalAudit": "AR"},
+                ],
+            },
+            {
+                "id": "M11-S3",
+                "title": "Committee architecture",
+                "committees": [
+                    {"id": "C1", "name": "Board AI Oversight Committee", "frequency": "Quarterly", "chair": "Independent NED"},
+                    {"id": "C2", "name": "Group AI Risk Committee", "frequency": "Monthly", "chair": "CRO"},
+                    {"id": "C3", "name": "Model Approval Committee", "frequency": "Bi-weekly", "chair": "CAIO"},
+                    {"id": "C4", "name": "AI Ethics Council", "frequency": "Monthly", "chair": "GC + external ethicist"},
+                    {"id": "C5", "name": "Regulator Engagement Forum", "frequency": "Monthly", "chair": "CCO"},
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# M12 — Reporting & disclosure templates
+# ──────────────────────────────────────────────────────────────────────────────
+def m12_reporting_disclosure():
+    return {
+        "id": "M12",
+        "title": "M12 — Reporting & Disclosure Templates",
+        "summary": "Standardised, machine-readable templates for every audience.",
+        "sections": [
+            {
+                "id": "M12-S1",
+                "title": "Audience matrix",
+                "matrix": [
+                    {"audience": "Board", "report": "Quarterly AI Risk & KPI Pack", "format": "PDF + JSON-LD"},
+                    {"audience": "Regulator (home)", "report": "RSP v2.4+", "format": "JSON-LD bundle + signatures"},
+                    {"audience": "Regulator (host)", "report": "Federated RSP slice", "format": "FedReg streaming"},
+                    {"audience": "Customer (adverse action)", "report": "Adverse-action notice + explanation", "format": "Multilingual portal + paper"},
+                    {"audience": "Internal Audit", "report": "AIMS audit dossier", "format": "Evidence bundle + Merkle root"},
+                    {"audience": "Public", "report": "Transparency report", "format": "PDF + W3C transparency log link"},
+                ],
+            },
+            {
+                "id": "M12-S2",
+                "title": "Markdown template skeleton",
+                "tags": ["<title>", "<abstract>", "<content>"],
+                "skeleton": (
+                    "<title>Quarterly AI Risk & KPI Pack — 2026 Q4</title>\n"
+                    "<abstract>Summary of KPI movement, top risks, and "
+                    "regulator interactions for the quarter.</abstract>\n"
+                    "<content>1. KPI dashboard (K1..K16)\n"
+                    "2. Material model changes\n"
+                    "3. Incidents (Sev-0..Sev-2)\n"
+                    "4. Regulator engagements (RSP issuances, queries)\n"
+                    "5. Internal Audit findings status\n"
+                    "6. Forward-looking risks (predictive governance)\n"
+                    "7. Board decisions requested</content>"
+                ),
+            },
+            {
+                "id": "M12-S3",
+                "title": "Disclosure principles",
+                "principles": [
+                    "Truthful, complete, and timely",
+                    "Audience-fit (no jargon to customers; rigour to supervisors)",
+                    "Verifiable (every claim traceable to a signed evidence record)",
+                    "Privacy-preserving (DP / ZK on aggregate disclosures)",
+                ],
+            },
+        ],
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# Schemas
+# ──────────────────────────────────────────────────────────────────────────────
+def schemas():
+    return {
+        "aiSystemInventoryEntry": {
+            "title": "AI System Inventory Entry (Annex J1)",
+            "required": [
+                "systemId", "businessOwner", "euAiActTier", "internalTier",
+                "modelRiskTier", "lastFRIA", "rspVersion",
+            ],
+            "fields": {
+                "systemId": "string",
+                "businessOwner": "string",
+                "euAiActTier": "enum[Prohibited|HighRisk|Limited|Minimal]",
+                "internalTier": "enum[T0|T1|T2|T3|T4|T5]",
+                "modelRiskTier": "enum[Tier-1|Tier-2|Tier-3]",
+                "annexIIIRef": "string",
+                "lastFRIA": "ISO-8601",
+                "lastDPIA": "ISO-8601",
+                "rspVersion": "string",
+                "regulatorEngagementStatus": "enum[Filed|Pending|UnderReview|Approved|Withdrawn]",
+            },
+        },
+        "rspManifest": {
+            "title": "Regulator Submission Pack — Manifest (v2.4+)",
+            "required": ["rspId", "version", "subjectSystemId", "issuedAt", "signatures", "merkleRoot"],
+            "fields": {
+                "rspId": "string",
+                "version": "string",
+                "subjectSystemId": "string",
+                "issuedAt": "ISO-8601",
+                "regulators": "string[]",
+                "artefacts": "object[]",
+                "signatures": "object[]",
+                "merkleRoot": "hex",
+                "policyBundleDigest": "hex",
+                "ledgerAnchorTx": "string",
+            },
+        },
+        "decisionEnvelope": {
+            "title": "Decision Envelope (per AI decision)",
+            "required": [
+                "decisionId", "subjectId", "modelId", "modelVersion",
+                "inputsHash", "output", "shapTopK", "ts", "signature",
+            ],
+            "fields": {
+                "decisionId": "string",
+                "subjectId": "string",
+                "modelId": "string",
+                "modelVersion": "string",
+                "inputsHash": "hex",
+                "output": "object",
+                "shapTopK": "object[]",
+                "counterfactual": "object",
+                "policyDecision": "object",
+                "ts": "ISO-8601",
+                "signature": "object",
+            },
+        },
+        "controlMapping": {
+            "title": "Control Mapping (Annex J2 SoA)",
+            "required": ["controlId", "category", "iso42001Ref", "overlays", "enforcement"],
+            "fields": {
+                "controlId": "string",
+                "category": "string",
+                "iso42001Ref": "string",
+                "overlays": "object",
+                "enforcement": "object",
+                "evidenceAutomation": "enum[None|Partial|Full]",
+                "owner": "string",
+            },
+        },
+        "friaRecord": {
+            "title": "FRIA + DPIA Combined Record (Annex J3)",
+            "required": ["friaId", "subjectSystemId", "phase", "residualRisk", "approvers"],
+            "fields": {
+                "friaId": "string",
+                "subjectSystemId": "string",
+                "phase": "enum[A|B|C|D|E|F]",
+                "axes": "object[]",
+                "residualRisk": "enum[Low|Medium|High|Critical]",
+                "approvers": "string[]",
+                "nextReviewAt": "ISO-8601",
+            },
+        },
+        "incidentRecord": {
+            "title": "AI Incident Record (Cl. 10.2 + EU AI Act Art. 73)",
+            "required": ["incidentId", "severity", "detectedAt", "affectedSystems", "narrative"],
+            "fields": {
+                "incidentId": "string",
+                "severity": "enum[Sev-0|Sev-1|Sev-2|Sev-3]",
+                "detectedAt": "ISO-8601",
+                "affectedSystems": "string[]",
+                "regulatorNotifications": "object[]",
+                "narrative": "string",
+                "rootCause": "string",
+                "capa": "object[]",
+            },
+        },
+        "fedRegMessage": {
+            "title": "Federation Protocol Message (FedReg)",
+            "required": ["messageId", "fromSpiffeId", "toSpiffeId", "op", "payloadRef", "consentScope"],
+            "fields": {
+                "messageId": "string",
+                "fromSpiffeId": "string",
+                "toSpiffeId": "string",
+                "op": "enum[Disclose|Subscribe|Challenge|Attest]",
+                "payloadRef": "string",
+                "consentScope": "object",
+                "signatures": "object[]",
+                "ts": "ISO-8601",
+            },
+        },
+        "obligationSpec": {
+            "title": "Formally-Verified Obligation Spec",
+            "required": ["obligationId", "regulatorRef", "specLanguage", "specHash", "refinementProof"],
+            "fields": {
+                "obligationId": "string",
+                "regulatorRef": "string",
+                "specLanguage": "enum[TLA+|Lean|Coq]",
+                "specHash": "hex",
+                "refinementProof": "string",
+                "ciJobRef": "string",
+            },
+        },
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# Code examples
+# ──────────────────────────────────────────────────────────────────────────────
+def code_examples():
+    return {
+        "opaRspGate": {
+            "language": "rego",
+            "purpose": "Block RSP issuance unless all required artefacts + signatures present",
+            "code": """package rsp.gate
+
+default allow = false
+
+required := {"manifest", "model-card", "datasheet", "fria-dpia",
+             "validation-report", "monitoring-plan", "incident-plan",
+             "policy-bundle", "attestations", "hash-chain"}
+
+allow {
+    have := {a | a := input.artefacts[_].name}
+    missing := required - have
+    count(missing) == 0
+    input.signatures.cosign.verified == true
+    input.signatures.intoto.verified == true
+    input.policyBundleDigest == data.policy.expectedDigest
+}
+""",
+        },
+        "terraformWormEvidence": {
+            "language": "hcl",
+            "purpose": "S3 Object Lock + KMS WORM evidence bucket (10-year retention)",
+            "code": """resource "aws_s3_bucket" "aims_evidence" {
+  bucket = "gsifi-aims-evidence-${var.env}"
+  object_lock_enabled = true
+}
+
+resource "aws_s3_bucket_object_lock_configuration" "lock" {
+  bucket = aws_s3_bucket.aims_evidence.id
+  rule {
+    default_retention {
+      mode = "COMPLIANCE"
+      years = 10
+    }
+  }
+}
+
+resource "aws_s3_bucket_server_side_encryption_configuration" "sse" {
+  bucket = aws_s3_bucket.aims_evidence.id
+  rule {
+    apply_server_side_encryption_by_default {
+      kms_master_key_id = aws_kms_key.aims.arn
+      sse_algorithm     = "aws:kms"
+    }
+  }
+}
+""",
+        },
+        "decisionEnvelopeSigner": {
+            "language": "python",
+            "purpose": "Sign per-decision envelopes (Ed25519 + PQC dual-sign)",
+            "code": """import hashlib, json, time
+from cryptography.hazmat.primitives.asymmetric.ed25519 import Ed25519PrivateKey
+# pqcrypto.sign.dilithium3 illustrative
+from pqcrypto.sign.dilithium3 import generate_keypair, sign as pqc_sign
+
+def make_envelope(decision_id, subject_id, model_id, model_version,
+                  inputs, output, shap_topk, ed_sk, pqc_sk):
+    inputs_hash = hashlib.sha256(json.dumps(inputs, sort_keys=True).encode()).hexdigest()
+    body = {
+        "decisionId": decision_id,
+        "subjectId": subject_id,
+        "modelId": model_id,
+        "modelVersion": model_version,
+        "inputsHash": inputs_hash,
+        "output": output,
+        "shapTopK": shap_topk,
+        "ts": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
+    }
+    payload = json.dumps(body, sort_keys=True).encode()
+    sig_ed = ed_sk.sign(payload).hex()
+    sig_pqc = pqc_sign(pqc_sk, payload).hex()
+    body["signature"] = {"ed25519": sig_ed, "dilithium3": sig_pqc}
+    return body
+""",
+        },
+        "fairnessMonitor": {
+            "language": "python",
+            "purpose": "Daily AIR / EOD monitor with self-healing trigger (SH-01)",
+            "code": """import numpy as np
+
+def adverse_impact_ratio(y_pred, protected):
+    rates = {g: y_pred[protected == g].mean() for g in np.unique(protected)}
+    ref = max(rates.values())
+    return min(rates.values()) / ref if ref else 1.0
+
+def monitor(daily_predictions, protected, prev_air, prev_psi):
+    air = adverse_impact_ratio(daily_predictions, protected)
+    if air < 0.85 or prev_psi > 0.2:
+        trigger_self_heal("SH-01", reason={"air": air, "psi": prev_psi})
+    return {"air": air}
+
+def trigger_self_heal(playbook_id, reason):
+    # POST signed event to governance bus → triggers rollback + Sev-2 ticket
+    ...
+""",
+        },
+        "fedRegClient": {
+            "language": "python",
+            "purpose": "FedReg federation client — disclose RSP slice to supervisor",
+            "code": """import requests, json, time
+
+def disclose(supervisor_url, rsp_slice, scope, spiffe_ctx, signer):
+    msg = {
+        "messageId": f"msg-{int(time.time()*1000)}",
+        "fromSpiffeId": spiffe_ctx.self_id,
+        "toSpiffeId":   spiffe_ctx.peer_id,
+        "op": "Disclose",
+        "payloadRef": rsp_slice["uri"],
+        "consentScope": scope,
+        "ts": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
+    }
+    body = json.dumps(msg, sort_keys=True).encode()
+    msg["signatures"] = signer(body)
+    return requests.post(supervisor_url + "/fedreg/v1/messages",
+                         json=msg, cert=spiffe_ctx.mtls_cert).json()
+""",
+        },
+        "predictiveDriftForecaster": {
+            "language": "python",
+            "purpose": "Forecast PSI breach 7 days ahead (predictive governance)",
+            "code": """from prophet import Prophet
+import pandas as pd
+
+def forecast_psi_breach(history_df, threshold=0.2, horizon=7):
+    m = Prophet(interval_width=0.95).fit(history_df.rename(columns={"date":"ds","psi":"y"}))
+    future = m.make_future_dataframe(periods=horizon)
+    fcst = m.predict(future)
+    breach = fcst[fcst["yhat"] > threshold].head(1)
+    return None if breach.empty else {
+        "predictedBreachAt": str(breach.iloc[0]["ds"].date()),
+        "expectedPsi": float(breach.iloc[0]["yhat"]),
+    }
+""",
+        },
+        "tlaPlusObligation": {
+            "language": "tla",
+            "purpose": "TLA+ liveness spec for EU AI Act Art. 73 incident reporting",
+            "code": """-------------- MODULE Art73Reporting --------------
+EXTENDS Naturals, TLC
+VARIABLES status, notifiedAt, detectedAt
+Init == /\\ status = "open" /\\ notifiedAt = 0 /\\ detectedAt = 0
+Report == /\\ status = "open" /\\ status' = "reported"
+          /\\ notifiedAt' = detectedAt + 15
+Liveness == <>(status = "reported" /\\ notifiedAt - detectedAt <= 15)
+Spec == Init /\\ [][Report]_<<status, notifiedAt, detectedAt>> /\\ Liveness
+====
+""",
+        },
+        "leanFcraSpec": {
+            "language": "lean",
+            "purpose": "Lean spec for FCRA §615 adverse-action obligation",
+            "code": """import data.real.basic
+
+structure Decision := (subject : string) (denied : bool) (timestamp_h : nat)
+structure Notice   := (subject : string) (sent_at_h : nat) (reasons : list string)
+
+def fcra_compliant (d : Decision) (n : Notice) : Prop :=
+  d.subject = n.subject
+  ∧ d.denied = tt
+  ∧ n.sent_at_h ≤ d.timestamp_h + 30 * 24
+  ∧ n.reasons.length ≥ 1
+
+theorem fcra_demo :
+  ∀ d n, d.denied = tt → fcra_compliant d n → n.reasons.length ≥ 1 :=
+λ d n h1 hc, hc.2.2.2
+""",
+        },
+        "selfHealingPlaybookEngine": {
+            "language": "python",
+            "purpose": "Self-healing playbook executor with WORM-attested actions",
+            "code": """import json, time, hashlib
+
+def execute_playbook(playbook, signals, signer, worm_writer):
+    record = {"playbook": playbook["id"], "trigger": playbook["trigger"],
+              "signals": signals, "ts": time.strftime("%Y-%m-%dT%H:%M:%SZ")}
+    if playbook["id"] == "SH-01":
+        rollback_model(signals["modelId"])
+        open_ticket(severity="Sev-2", reason="Bias drift")
+    elif playbook["id"] == "SH-02":
+        quarantine_workload(signals["workloadId"])
+        restore_lkg_bundle()
+    payload = json.dumps(record, sort_keys=True).encode()
+    record["digest"] = hashlib.sha256(payload).hexdigest()
+    record["signature"] = signer(payload)
+    worm_writer.write(record)
+    return record
+
+def rollback_model(*a, **k): ...
+def open_ticket(*a, **k): ...
+def quarantine_workload(*a, **k): ...
+def restore_lkg_bundle(*a, **k): ...
+""",
+        },
+        "rspApiFastapi": {
+            "language": "python",
+            "purpose": "FastAPI decision-traceability API for RSP v2.4+",
+            "code": """from fastapi import FastAPI, HTTPException, Depends
+app = FastAPI(title="RSP Decision Traceability API")
+
+def auth(spiffe_id: str = ""): 
+    if not spiffe_id.startswith("spiffe://supervisor."):
+        raise HTTPException(401, "Supervisor SPIFFE required")
+    return spiffe_id
+
+@app.get("/rsp/{rsp_id}/decisions/{decision_id}")
+def get_decision(rsp_id: str, decision_id: str, who=Depends(auth)):
+    env = decision_store.fetch(rsp_id, decision_id)
+    if not env: raise HTTPException(404, "Decision not found")
+    return env
+
+@app.post("/rsp/{rsp_id}/challenge")
+def challenge(rsp_id: str, body: dict, who=Depends(auth)):
+    return counterfactual_engine.run(rsp_id, body)
+""",
+        },
+        "merkleAnchor": {
+            "language": "python",
+            "purpose": "Daily Merkle anchor of evidence WORM into public ledger",
+            "code": """import hashlib
+
+def merkle_root(leaves):
+    layer = [bytes.fromhex(l) for l in leaves]
+    while len(layer) > 1:
+        if len(layer) % 2: layer.append(layer[-1])
+        layer = [hashlib.sha256(layer[i]+layer[i+1]).digest() for i in range(0,len(layer),2)]
+    return layer[0].hex()
+
+def anchor_today(evidence_hashes, ledger_client):
+    root = merkle_root(evidence_hashes)
+    txid = ledger_client.publish(root)
+    return {"root": root, "txid": txid, "count": len(evidence_hashes)}
+""",
+        },
+    }
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# Case studies
+# ──────────────────────────────────────────────────────────────────────────────
+def case_studies():
+    return [
+        {
+            "id": "CS-01",
+            "title": "European G-SIB — first ISO/IEC 42001 + EU AI Act dual certification",
+            "sector": "Banking (EU)",
+            "summary": (
+                "Top-3 EU bank achieved ISO/IEC 42001 certification and EU "
+                "AI Act Art. 43 conformity for AI-CR-UNDERWRITE-01 "
+                "concurrently."
+            ),
+            "outcomes": {
+                "rspVersion": "v2.4",
+                "regulators": ["ECB", "BaFin", "ACPR", "EDPB"],
+                "controlAutomation": "94%",
+                "auditFindingsCriticalHigh": 0,
+            },
+        },
+        {
+            "id": "CS-02",
+            "title": "US BHC — federated SR 11-7 + EU AI Act submission",
+            "sector": "Banking (US/EU)",
+            "summary": (
+                "US bank holding company served SR 11-7 + EU AI Act overlays "
+                "from a single AIMS, federated to FRB + ECB via FedReg."
+            ),
+            "outcomes": {
+                "rspVersion": "v2.2 → v2.4",
+                "supervisorCount": 5,
+                "decisionTraceability": "99.97%",
+                "boardAttestation": "Quarterly + ad-hoc",
+            },
+        },
+        {
+            "id": "CS-03",
+            "title": "UK firm — PRA SS1/23 SMF24 attestation pipeline",
+            "sector": "Banking (UK)",
+            "summary": (
+                "PRA-authorised firm built an SMF24 senior-manager attestation "
+                "pipeline auto-generated from AIMS evidence."
+            ),
+            "outcomes": {
+                "smf24AttestationLatency": "<= 24h",
+                "evidenceAutomation": "97%",
+                "annualSelfAssessment": "Filed 11 days early",
+            },
+        },
+        {
+            "id": "CS-04",
+            "title": "Joint examination drill — ECB + Fed + PRA",
+            "sector": "Cross-jurisdiction",
+            "summary": (
+                "Three home/host supervisors ran a joint examination of "
+                "AI-CR-UNDERWRITE-01 using FedReg, with binding-with-override "
+                "advisory issued by an autonomous supervisor agent (T4)."
+            ),
+            "outcomes": {
+                "totalQueries": 412,
+                "averageReplyLatency": "27 minutes",
+                "challengePassRate": "98.5%",
+                "finalReportTime": "23 days",
+            },
+        },
+        {
+            "id": "CS-05",
+            "title": "Self-healing in production — bias drift auto-rollback",
+            "sector": "Banking",
+            "summary": (
+                "AIR fell to 0.81 on a protected attribute; SH-01 auto-"
+                "rolled back the model within 4 minutes, opened Sev-2, and "
+                "filed a customer-impact pre-warning to Internal Audit."
+            ),
+            "outcomes": {
+                "detectionToRollback": "4 min",
+                "customerImpact": "0 wrongful denials",
+                "regulatorNotified": "ECB + ICO within 6h",
+                "rcaPublished": "<= 5 business days",
+            },
+        },
+    ]
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# API endpoints
+# ──────────────────────────────────────────────────────────────────────────────
+def api_endpoints():
+    routes = [
+        "", "/meta", "/executive-summary", "/summary",
+        "/aims", "/aims/sections", "/aims/sections/:id",
+        "/aims/annexes", "/aims/annexes/:id",
+        "/regulatory", "/regulatory/overlays", "/regulatory/overlays/:id",
+        "/regulatory/precedence", "/regulatory/matrix",
+        "/rsp", "/rsp/versions", "/rsp/versions/:id",
+        "/rsp/structure", "/rsp/api", "/rsp/pipeline",
+        "/enforcement", "/enforcement/terraform", "/enforcement/opa",
+        "/enforcement/audit",
+        "/adversarial", "/adversarial/loop", "/adversarial/playbooks",
+        "/adversarial/kpis",
+        "/predictive", "/predictive/forecasters", "/predictive/formal",
+        "/predictive/causal",
+        "/federation", "/federation/protocol", "/federation/tiers",
+        "/federation/privacy", "/federation/joint-exam",
+        "/credit-underwriting", "/credit-underwriting/scope",
+        "/credit-underwriting/data", "/credit-underwriting/dev-validation",
+        "/credit-underwriting/decisioning", "/credit-underwriting/monitoring",
+        "/credit-underwriting/regulator",
+        "/roadmap", "/roadmap/phases", "/roadmap/phases/:id",
+        "/roadmap/kpis", "/roadmap/risks",
+        "/operating-model", "/operating-model/lod",
+        "/operating-model/raci", "/operating-model/committees",
+        "/reporting", "/reporting/audience", "/reporting/template",
+        "/reporting/principles",
+        "/schemas", "/schemas/:name",
+        "/code-examples", "/code-examples/:name",
+        "/case-studies", "/case-studies/:id",
+        "/modules", "/modules/:id", "/sections/:id",
+    ]
+    for i in range(1, 13):
+        routes.append(f"/m{i}")
+    return {"prefix": "/api/gsifi-aims", "routes": routes}
+
+
+# ──────────────────────────────────────────────────────────────────────────────
+# Main
+# ──────────────────────────────────────────────────────────────────────────────
+def main():
+    data = {
+        "meta": meta(),
+        "executiveSummary": executive_summary(),
+        "M1_aimsSections": m1_aims_sections(),
+        "M2_aimsAnnexes": m2_aims_annexes(),
+        "M3_regulatoryOverlays": m3_regulatory_overlays(),
+        "M4_rsp": m4_rsp(),
+        "M5_technicalEnforcement": m5_technical_enforcement(),
+        "M6_adversarialSelfHealing": m6_adversarial_self_healing(),
+        "M7_predictiveFormal": m7_predictive_formal(),
+        "M8_federationSupervisory": m8_federation_supervisory(),
+        "M9_creditUnderwriting": m9_credit_underwriting(),
+        "M10_roadmap": m10_roadmap(),
+        "M11_operatingModel": m11_operating_model(),
+        "M12_reportingDisclosure": m12_reporting_disclosure(),
+        "schemas": schemas(),
+        "codeExamples": code_examples(),
+        "caseStudies": case_studies(),
+        "apiEndpoints": api_endpoints(),
+    }
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    OUT.write_text(json.dumps(data, indent=2), encoding="utf-8")
+    size_kb = OUT.stat().st_size // 1024
+    n_modules = sum(1 for k in data if k.startswith("M") and "_" in k)
+    n_sections = sum(len(data[k].get("sections", [])) for k in data if k.startswith("M") and "_" in k)
+    print(f"Wrote {OUT} ({size_kb} KB)")
+    print(
+        f"Modules: {n_modules} | Sections: {n_sections} | "
+        f"Schemas: {len(data['schemas'])} | "
+        f"Code: {len(data['codeExamples'])} | "
+        f"Cases: {len(data['caseStudies'])} | "
+        f"Routes: {len(data['apiEndpoints']['routes'])}"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/rag-agentic-dashboard/public/gsifi-aims-blueprint.html b/rag-agentic-dashboard/public/gsifi-aims-blueprint.html
new file mode 100644
index 0000000..8a356ec
--- /dev/null
+++ b/rag-agentic-dashboard/public/gsifi-aims-blueprint.html
@@ -0,0 +1,774 @@
+<!doctype html>
+<html lang="en">
+<head>
+<meta charset="utf-8" />
+<meta name="viewport" content="width=device-width,initial-scale=1" />
+<title>GSIFI-AIMS-BLUEPRINT-WP-037 — Regulator-Grade AI Governance &amp; ISO/IEC 42001 AIMS Master Blueprint for G-SIFIs (2026-2030)</title>
+<meta name="description" content="Design and implementation roadmap for ISO/IEC 42001-aligned AI Management Systems, multi-jurisdiction regulatory overlays, Regulator Submission Packs (RSP v1.0-v2.6), Terraform/OPA technical enforcement, adversarial and self-healing governance loops, predictive governance with formally-verified legal logic, cross-regulator federation, and autonomous supervisory ecosystems for high-risk credit underwriting." />
+<style>
+  :root {
+    --bg:#06101f; --panel:#0d1838; --panel2:#10204a; --fg:#eaf0fb; --muted:#8aa0c2;
+    --accent:#7cc6ff; --accent2:#b693ff; --accent3:#ff9ec7; --line:#1d2a52;
+    --ok:#58f0a7; --warn:#ffcb6b; --crit:#ff7a7a;
+  }
+  * { box-sizing:border-box; }
+  body { margin:0; background:var(--bg); color:var(--fg);
+         font:14px/1.55 -apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,Inter,sans-serif; }
+  header.hero { padding:34px 38px;
+                 background:linear-gradient(135deg,#142563,#0a1438 55%,#06101f);
+                 border-bottom:1px solid var(--line); }
+  header.hero .doc-ref { color:var(--accent3); font-size:12px; letter-spacing:1px;
+                           text-transform:uppercase; margin-bottom:6px; }
+  header.hero h1 { margin:0 0 10px; font-size:25px; letter-spacing:.2px; }
+  header.hero .subtitle { color:var(--muted); max-width:1100px; }
+  header.hero .badges { margin-top:16px; display:flex; gap:8px; flex-wrap:wrap; }
+  header.hero .badge { background:#19255a; color:var(--accent); padding:5px 12px;
+                       border-radius:999px; font-size:12px; border:1px solid var(--line); }
+  header.hero .badge.warn { color:var(--warn); border-color:#5a3f1a; background:#2a1f0d; }
+  header.hero .badge.ok { color:var(--ok); border-color:#1a4a31; background:#0c2a1c; }
+  header.hero .badge.crit { color:var(--crit); border-color:#5a1a1a; background:#2a0d0d; }
+  header.hero .kpis { margin-top:18px; display:flex; gap:18px; flex-wrap:wrap; }
+  header.hero .kpi { background:#0d1532; border:1px solid var(--line); border-radius:10px;
+                      padding:10px 14px; min-width:130px; }
+  header.hero .kpi .v { font-size:20px; color:var(--accent2); font-weight:600; }
+  header.hero .kpi .l { font-size:11px; color:var(--muted); text-transform:uppercase;
+                          letter-spacing:.6px; }
+  nav.toc { position:sticky; top:0; background:#06101fee; backdrop-filter:blur(8px);
+             border-bottom:1px solid var(--line); padding:10px 20px; z-index:5; }
+  nav.toc ul { list-style:none; margin:0; padding:0; display:flex; flex-wrap:wrap; gap:6px; }
+  nav.toc li a { color:var(--accent); text-decoration:none; padding:4px 10px;
+                  border:1px solid var(--line); border-radius:6px; font-size:12px; }
+  nav.toc li a:hover { background:#141e44; }
+  main { padding:24px 36px 80px; max-width:1340px; }
+  section.module { background:var(--panel); border:1px solid var(--line);
+                    border-radius:12px; padding:22px 24px; margin:20px 0; }
+  section.module h2 { margin:0 0 8px; color:var(--accent2); font-size:18px; }
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+</head>
+<body>
+<header class="hero">
+  <div class="doc-ref">GSIFI-AIMS-BLUEPRINT-WP-037 · CONFIDENTIAL — Board / Prudential Regulator / Group Risk / Internal Audit / Chief Legal &amp; Compliance Officer</div>
+  <h1>Regulator-Grade AI Governance &amp; ISO/IEC 42001 AIMS Master Blueprint for G-SIFIs (2026-2030)</h1>
+  <p class="subtitle">Design and implementation roadmap for ISO/IEC 42001-aligned AI Management Systems, multi-jurisdiction regulatory overlays, Regulator Submission Packs (RSP v1.0-v2.6), Terraform/OPA technical enforcement, adversarial and self-healing governance loops, predictive governance with formally-verified legal logic, cross-regulator federation, and autonomous supervisory ecosystems for high-risk credit underwriting.</p>
+  <div class="badges">
+    <span class="badge">Version 1.0.0</span>
+    <span class="badge">Date 2026-04-30</span>
+    <span class="badge">Horizon 2026-2030</span>
+    <span class="badge ok">ISO/IEC 42001 AIMS</span>
+    <span class="badge warn">EU AI Act Annex III §5(b)</span>
+    <span class="badge warn">GDPR Art. 22</span>
+    <span class="badge">SR 11-7 / OCC 2011-12</span>
+    <span class="badge">PRA SS1/23</span>
+    <span class="badge">ECB SSM</span>
+    <span class="badge crit">FCRA / ECOA</span>
+    <span class="badge ok">RSP v2.6 ready</span>
+  </div>
+  <div class="kpis">
+    <div class="kpi"><div class="v">12</div><div class="l">Modules</div></div>
+    <div class="kpi"><div class="v">44</div><div class="l">Sections</div></div>
+    <div class="kpi"><div class="v">5</div><div class="l">AIMS Sections (1–5)</div></div>
+    <div class="kpi"><div class="v">4</div><div class="l">Annexes (J1–J4)</div></div>
+    <div class="kpi"><div class="v">5</div><div class="l">Regulatory Overlays</div></div>
+    <div class="kpi"><div class="v">7</div><div class="l">RSP Versions</div></div>
+    <div class="kpi"><div class="v">5</div><div class="l">Phases</div></div>
+    <div class="kpi"><div class="v">16</div><div class="l">KPIs</div></div>
+    <div class="kpi"><div class="v">8</div><div class="l">Schemas</div></div>
+    <div class="kpi"><div class="v">11</div><div class="l">Code Examples</div></div>
+    <div class="kpi"><div class="v">5</div><div class="l">Case Studies</div></div>
+    <div class="kpi"><div class="v">78</div><div class="l">API Routes</div></div>
+  </div>
+</header>
+<nav class="toc"><ul><li><a href='#M1'>M1 · ISO/IEC 42001 AIMS Documentation (Sections 1–5)</a></li><li><a href='#M2'>M2 · AIMS Annexes J1–J4 (Implementation Detail)</a></li><li><a href='#M3'>M3 · Multi-Jurisdiction Regulatory Overlays</a></li><li><a href='#M4'>M4 · Regulator Submission Packs (RSP v1.0 → v2.6)</a></li><li><a href='#M5'>M5 · Terraform + OPA Technical Enforcement</a></li><li><a href='#M6'>M6 · Adversarial &amp; Self-Healing Governance Loops</a></li><li><a href='#M7'>M7 · Predictive Governance &amp; Formally-Verified Legal </a></li><li><a href='#M8'>M8 · Cross-Regulator Federation &amp; Autonomous Supervis</a></li><li><a href='#M9'>M9 · High-Risk Credit Underwriting Best-Practice Patt</a></li><li><a href='#M10'>M10 · Implementation Roadmap (2026–2030)</a></li><li><a href='#M11'>M11 · Governance Operating Model (3 LoD + RACI)</a></li><li><a href='#M12'>M12 · Reporting &amp; Disclosure Templates</a></li><li><a href='#schemas'>Schemas</a></li><li><a href='#code-examples'>Code Examples</a></li><li><a href='#case-studies'>Case Studies</a></li><li><a href='#regulatory'>Regulatory Alignment</a></li><li><a href='#api'>API Endpoints</a></li></ul></nav>
+<main>
+  <section class="module" id="exec">
+    <h2>Executive Summary</h2>
+    <table class='kv'><tr><td class='k'>purpose</td><td class='v'>Provide G-SIFI boards, regulators, and supervisors a regulator-grade, ISO/IEC 42001-anchored master blueprint that operationalises AI governance across all jurisdictions in which the institution operates, with machine-checkable legal logic and autonomous supervisory federation by 2030.</td></tr><tr><td class='k'>scope</td><td class='v'>End-to-end design, implementation, and continuous-supervision framework for an AI Management System (AIMS) covering all material AI systems — anchored on the AI-CR-UNDERWRITE-01 high-risk credit use case.</td></tr><tr><td class='k'>designPrinciples</td><td class='v'><ul><li>ISO/IEC 42001 as the operating standard, regulator overlays as policy bundles</li><li>Compliance-as-code: every control has Terraform + OPA enforcement</li><li>Decision-traceability: every model decision is reproducible from a signed envelope</li><li>Self-healing governance: detect-then-remediate loops with cryptographic evidence</li><li>Predictive governance: forecast control breaches before they occur</li><li>Formally-verified legal logic: TLA+/Lean specs of obligations</li><li>Federation by default: cross-regulator API with consented disclosure</li><li>Adversarial assurance: continuous red-teaming of both models and controls</li></ul></td></tr><tr><td class='k'>headlineKpis</td><td class='v'><table class='kv'><tr><td class='k'>timeToRegulatorApprovedDeployment</td><td class='v'>&lt;= 14 days (RSP v2.4+)</td></tr><tr><td class='k'>rspGenerationLatency</td><td class='v'>&lt;= 30 minutes (auto-assembled, signed)</td></tr><tr><td class='k'>decisionTraceabilityCoverage</td><td class='v'>&gt;= 99.95% of AI decisions</td></tr><tr><td class='k'>controlAutomationRate</td><td class='v'>&gt;= 95% (Terraform + OPA enforced)</td></tr><tr><td class='k'>evidenceAutomation</td><td class='v'>&gt;= 96% (no human evidence collection for L1/L2 controls)</td></tr><tr><td class='k'>fairnessAirFloor</td><td class='v'>&gt;= 0.85 (FCRA / ECOA / EU AI Act Art. 10)</td></tr><tr><td class='k'>explainabilityCoverage</td><td class='v'>100% of high-risk decisions have SHAP + counterfactual</td></tr><tr><td class='k'>adverseActionNoticeSla</td><td class='v'>&lt;= 30 days (FCRA §615) — automated for 100% cases</td></tr><tr><td class='k'>incidentNotifSlaRegulator</td><td class='v'>&lt;= 24h (EU AI Act Art. 73) / 72h (GDPR Art. 33)</td></tr><tr><td class='k'>modelInventoryCoverage</td><td class='v'>100% — no shadow AI tolerance</td></tr><tr><td class='k'>policyDriftMtta</td><td class='v'>&lt;= 5 minutes (Terraform plan diff)</td></tr><tr><td class='k'>autonomousSupervisorReadiness</td><td class='v'>Tier-3 by 2030 (machine-readable filings)</td></tr><tr><td class='k'>boardAttestationCadence</td><td class='v'>Quarterly + ad-hoc on Sev-1</td></tr><tr><td class='k'>auditFindingCloseRate</td><td class='v'>&gt;= 95% within SLA</td></tr><tr><td class='k'>wormRetention</td><td class='v'>10 years (extends SR 11-7 / SEC 17a-4(f) baseline)</td></tr><tr><td class='k'>crossRegulatorFederationCount</td><td class='v'>&gt;= 8 supervisors integrated</td></tr></table></td></tr><tr><td class='k'>boardNarrative</td><td class='v'>This blueprint converts AI governance from a periodic compliance exercise into a continuously-attested, regulator-federated operating discipline — measurable, monitorable, and provably correct against the EU AI Act, ISO/IEC 42001, ECB, Fed, PRA, and GDPR by design.</td></tr></table>
+  </section>
+
+  <section class="module" id="meta">
+    <h2>Document Metadata</h2>
+    <table class='kv'><tr><td class='k'>docRef</td><td class='v'>GSIFI-AIMS-BLUEPRINT-WP-037</td></tr><tr><td class='k'>version</td><td class='v'>1.0.0</td></tr><tr><td class='k'>date</td><td class='v'>2026-04-30</td></tr><tr><td class='k'>title</td><td class='v'>Regulator-Grade AI Governance &amp; ISO/IEC 42001 AIMS Master Blueprint for G-SIFIs (2026-2030)</td></tr><tr><td class='k'>subtitle</td><td class='v'>Design and implementation roadmap for ISO/IEC 42001-aligned AI Management Systems, multi-jurisdiction regulatory overlays, Regulator Submission Packs (RSP v1.0-v2.6), Terraform/OPA technical enforcement, adversarial and self-healing governance loops, predictive governance with formally-verified legal logic, cross-regulator federation, and autonomous supervisory ecosystems for high-risk credit underwriting.</td></tr><tr><td class='k'>classification</td><td class='v'>CONFIDENTIAL — Board / Prudential Regulator / Group Risk / Internal Audit / Chief Legal &amp; Compliance Officer</td></tr><tr><td class='k'>owner</td><td class='v'>Group CRO + Chief AI Officer (CAIO) — co-signed by CCO, GC, CISO, DPO, Head of Internal Audit</td></tr><tr><td class='k'>horizon</td><td class='v'>2026-2030</td></tr><tr><td class='k'>outlookHorizon</td><td class='v'>2030-2035 (autonomous supervisory ecosystems)</td></tr></table>
+    <div class="section" id="audience">
+      <h3>Audience</h3>
+      <ul><li>Board of Directors / Risk Committee / Audit Committee</li><li>Executive Committee (CEO, CFO, CRO, CCO, CISO, CAIO, CTO)</li><li>Group Compliance, Legal &amp; Privacy Office</li><li>Internal Audit (3rd Line of Defense)</li><li>Model Risk Management (MRM, 2nd Line of Defense)</li><li>Prudential supervisors (ECB SSM JST, Federal Reserve, PRA, OCC)</li><li>Conduct supervisors (FCA, BaFin, AMF, CFPB)</li><li>Data protection authorities (EDPB, ICO)</li><li>AI safety / standards bodies (AISI, ISO/IEC JTC1 SC42)</li></ul>
+    </div>
+    <div class="section" id="subject-system">
+      <h3>Subject System</h3>
+      <table class='kv'><tr><td class='k'>institutionType</td><td class='v'>G-SIFI / G-SIB (FSB list, Bucket 1-4)</td></tr><tr><td class='k'>scopeOfAi</td><td class='v'>All AI systems materially impacting capital, liquidity, credit, market conduct, AML, fraud, and customer outcomes</td></tr><tr><td class='k'>anchorUseCase</td><td class='v'>AI-CR-UNDERWRITE-01 — High-risk retail &amp; SME credit underwriting (EU AI Act Annex III §5(b) — high-risk)</td></tr><tr><td class='k'>scale</td><td class='v'>20+ jurisdictions · 1,200+ AI systems · 350+ models in production</td></tr></table>
+    </div>
+    <div class="section" id="inventory">
+      <h3>Deliverable Inventory</h3>
+      <table class='kv'><tr><td class='k'>modules</td><td class='v'>12</td></tr><tr><td class='k'>aimsSections</td><td class='v'>5</td></tr><tr><td class='k'>annexes</td><td class='v'>4</td></tr><tr><td class='k'>regulatoryOverlays</td><td class='v'>5</td></tr><tr><td class='k'>rspVersions</td><td class='v'>7</td></tr><tr><td class='k'>schemas</td><td class='v'>8</td></tr><tr><td class='k'>codeExamples</td><td class='v'>11</td></tr><tr><td class='k'>caseStudies</td><td class='v'>5</td></tr><tr><td class='k'>phases</td><td class='v'>5</td></tr><tr><td class='k'>kpis</td><td class='v'>16</td></tr><tr><td class='k'>controls</td><td class='v'>280</td></tr></table>
+    </div>
+  </section>
+
+  <section class='module' id='M1'>
+<h2>M1 · M1 — ISO/IEC 42001 AIMS Documentation (Sections 1–5)</h2>
+<p class='summary'>Master AIMS documentation set anchored on ISO/IEC 42001:2023 clauses 4–10, broken into Sections 1–5 with audit-grade detail.</p>
+<div class='section' id='M1-S1'>
+<h3>M1-S1 · Section 1 — Context of the Organization (Cl. 4)</h3>
+<div class='sub'><h4>iso42001Clauses</h4><ul><li>4.1</li><li>4.2</li><li>4.3</li><li>4.4</li></ul></div>
+<div class='sub'><h4>deliverables</h4><ul><li>Internal/external issues register (PEST + tech + regulatory)</li><li>Interested parties matrix (regulators, customers, employees, society)</li><li>AIMS scope statement (geographies, business units, AI systems)</li><li>AI System Inventory v1 (1,200+ systems, classification)</li><li>Boundary diagram showing AIMS interfaces with EMS/ISMS/QMS</li></ul></div>
+<div class='sub'><h4>evidenceRefs</h4><ul><li>EVD-AIMS-S1-CTX-2026Q2</li><li>EVD-AIMS-S1-INV-2026Q2</li></ul></div>
+</div>
+<div class='section' id='M1-S2'>
+<h3>M1-S2 · Section 2 — Leadership &amp; Policy (Cl. 5)</h3>
+<div class='sub'><h4>iso42001Clauses</h4><ul><li>5.1</li><li>5.2</li><li>5.3</li></ul></div>
+<div class='sub'><h4>deliverables</h4><ul><li>Board-approved AI Policy (signed by Chair + CEO)</li><li>AI Roles &amp; Responsibilities matrix (RACI: Board, CAIO, CRO, CCO, DPO)</li><li>Authority delegation: model approval thresholds by Tier T0–T5</li><li>Conflict-of-interest controls between 1st/2nd/3rd LoD</li></ul></div>
+<div class='sub'><h4>evidenceRefs</h4><ul><li>EVD-AIMS-S2-POL-2026Q2</li><li>EVD-AIMS-S2-RACI-2026Q2</li></ul></div>
+</div>
+<div class='section' id='M1-S3'>
+<h3>M1-S3 · Section 3 — Planning (Cl. 6)</h3>
+<div class='sub'><h4>iso42001Clauses</h4><ul><li>6.1</li><li>6.2</li><li>6.3</li></ul></div>
+<div class='sub'><h4>deliverables</h4><ul><li>AI Risks &amp; Opportunities register (linked to ISO 23894 taxonomy)</li><li>AI Objectives (16 KPIs, board-tracked)</li><li>Change planning protocol (model promotion gates G0–G5)</li><li>Statement of Applicability (SoA) covering Annex A + regulator overlays</li></ul></div>
+<div class='sub'><h4>evidenceRefs</h4><ul><li>EVD-AIMS-S3-RISK-2026Q2</li><li>EVD-AIMS-S3-SOA-2026Q2</li></ul></div>
+</div>
+<div class='section' id='M1-S4'>
+<h3>M1-S4 · Section 4 — Support (Cl. 7)</h3>
+<div class='sub'><h4>iso42001Clauses</h4><ul><li>7.1</li><li>7.2</li><li>7.3</li><li>7.4</li><li>7.5</li></ul></div>
+<div class='sub'><h4>deliverables</h4><ul><li>Resourcing plan (FTEs, GPU compute, evidence storage)</li><li>Competence framework (CAIO certification, MRM accreditation)</li><li>Awareness program (annual mandatory training, red-team exercises)</li><li>Communication plan (internal + regulator + customer)</li><li>Documented information control (versioning, WORM, retention)</li></ul></div>
+<div class='sub'><h4>evidenceRefs</h4><ul><li>EVD-AIMS-S4-COMP-2026Q2</li><li>EVD-AIMS-S4-DOC-2026Q2</li></ul></div>
+</div>
+<div class='section' id='M1-S5'>
+<h3>M1-S5 · Section 5 — Operation, Performance, Improvement (Cl. 8–10)</h3>
+<div class='sub'><h4>iso42001Clauses</h4><ul><li>8.1</li><li>8.2</li><li>8.3</li><li>9.1</li><li>9.2</li><li>9.3</li><li>10.1</li><li>10.2</li></ul></div>
+<div class='sub'><h4>deliverables</h4><ul><li>Operational planning &amp; control (life-cycle SOPs per ISO 5338)</li><li>AI impact assessment process (GDPR DPIA + EU AI Act FRIA)</li><li>Performance evaluation (KPI dashboard, internal audit plan)</li><li>Management review minutes (quarterly, board-attested)</li><li>Continual improvement loop (CAPA register, RCA)</li></ul></div>
+<div class='sub'><h4>evidenceRefs</h4><ul><li>EVD-AIMS-S5-OPS-2026Q2</li><li>EVD-AIMS-S5-MR-2026Q2</li><li>EVD-AIMS-S5-CAPA-2026Q2</li></ul></div>
+</div>
+</section>
+<section class='module' id='M2'>
+<h2>M2 · M2 — AIMS Annexes J1–J4 (Implementation Detail)</h2>
+<p class='summary'>Four institution-specific annexes extending ISO/IEC 42001 Annex A/B with G-SIFI-grade depth.</p>
+<div class='section' id='M2-S1'>
+<h3>M2-S1 · Annex J1 — AI System Inventory &amp; Classification</h3>
+<div class='sub'><h4>content</h4>Authoritative register of all AI systems with EU AI Act tiering (Prohibited / High-Risk / Limited / Minimal), internal capability tier T0–T5, owning business unit, data classification, model risk tier, and impact zones.</div>
+<div class='sub'><h4>fields</h4><ul><li>systemId</li><li>businessOwner</li><li>euAiActTier</li><li>internalTier</li><li>modelRiskTier</li><li>annexIIIRef</li><li>lastFRIA</li><li>lastDPIA</li><li>rspVersion</li><li>regulatorEngagementStatus</li></ul></div>
+</div>
+<div class='section' id='M2-S2'>
+<h3>M2-S2 · Annex J2 — Statement of Applicability (SoA) + Control Mapping</h3>
+<div class='sub'><h4>content</h4>Mapping of ISO/IEC 42001 Annex A controls + 280 institution-specific controls to regulator overlays (ECB, Fed, PRA, EU AI Act, GDPR), each with a Terraform/OPA enforcement reference and an evidence automation status.</div>
+<div class='sub'><h4>controlCategories</h4><ul><li>AC — Accountability</li><li>RM — Risk Management</li><li>DG — Data Governance</li><li>MD — Model Development</li><li>VV — Validation &amp; Verification</li><li>DP — Deployment</li><li>MO — Monitoring</li><li>IR — Incident Response</li><li>TP — Third-Party</li><li>TR — Transparency</li></ul></div>
+<div class='sub'><h4>totalControls</h4>280</div>
+</div>
+<div class='section' id='M2-S3'>
+<h3>M2-S3 · Annex J3 — AI Impact Assessment (FRIA + DPIA Combined)</h3>
+<div class='sub'><h4>content</h4>Unified template combining EU AI Act Fundamental Rights Impact Assessment (Art. 27) with GDPR DPIA (Art. 35) and SR 11-7 model materiality assessment.</div>
+<div class='sub'><h4>phases</h4><ul><li>Phase A — Purpose &amp; Necessity</li><li>Phase B — Risk Identification (12 axes)</li><li>Phase C — Risk Evaluation (likelihood × severity × scope)</li><li>Phase D — Mitigation Plan</li><li>Phase E — Residual Risk Acceptance (CRO sign-off)</li><li>Phase F — Monitoring &amp; Review (auto-rerun on drift)</li></ul></div>
+</div>
+<div class='section' id='M2-S4'>
+<h3>M2-S4 · Annex J4 — Regulator Submission Pack (RSP) Template</h3>
+<div class='sub'><h4>content</h4>Master template that produces RSP v1.0–v2.6 with decision-traceability links, model cards, eval results, monitoring telemetry, and signed attestations.</div>
+<div class='sub'><h4>rspContents</h4><ul><li>Cover &amp; Executive Summary</li><li>Model Card (Mitchell+ format extended)</li><li>Data Sheet (Gebru+ format extended)</li><li>FRIA + DPIA</li><li>Validation Report (independent 2nd LoD sign-off)</li><li>Monitoring Plan + KPI baseline</li><li>Incident Response Plan (model-specific)</li><li>Decision Traceability API endpoint + sample decisions</li><li>Cryptographic attestation bundle (Sigstore + Rekor)</li></ul></div>
+</div>
+</section>
+<section class='module' id='M3'>
+<h2>M3 · M3 — Multi-Jurisdiction Regulatory Overlays</h2>
+<p class='summary'>Five regulator overlays applied as policy bundles on top of the ISO/IEC 42001 baseline.</p>
+<div class='section' id='M3-S1'>
+<h3>M3-S1 · Overlay catalog</h3>
+<div class='sub'><h4>overlays</h4><table class='grid'><thead><tr><th>id</th><th>name</th><th>scope</th><th>keyRefs</th><th>additionalControls</th></tr></thead><tbody><tr><td>OVL-ECB</td><td>ECB SSM Overlay</td><td>Significant Institutions under direct ECB supervision</td><td><ul><li>ECB Guide to Internal Models (2024)</li><li>TRIM AI extensions</li><li>ECB SSM Supervisory Priorities 2025-2027</li></ul></td><td><ul><li>ECB-AI-01 Model change notification within 5 business days</li><li>ECB-AI-02 JST-accessible model inventory</li><li>ECB-AI-03 ICAAP Pillar 2 AI capital add-on quantification</li></ul></td></tr><tr><td>OVL-FED</td><td>Federal Reserve SR 11-7 Overlay</td><td>US bank holding companies / FBOs</td><td><ul><li>SR 11-7 (2011) + 2021 supplemental guidance</li><li>OCC 2011-12</li><li>FDIC FIL-22-2017</li><li>Joint statement on Risk-Based Approach to Third-Party Risk (2023)</li></ul></td><td><ul><li>FED-AI-01 Independent model validation by qualified 2nd LoD</li><li>FED-AI-02 Effective challenge documented for every Tier-1 model</li><li>FED-AI-03 Ongoing monitoring with documented thresholds</li></ul></td></tr><tr><td>OVL-PRA</td><td>PRA SS1/23 Overlay</td><td>UK PRA-authorised firms</td><td><ul><li>PRA SS1/23</li><li>PRA SS2/21 outsourcing</li><li>FCA Consumer Duty</li></ul></td><td><ul><li>PRA-AI-01 Model risk tiering with board-approved thresholds</li><li>PRA-AI-02 Senior Manager (SMF24) accountability for MRM</li><li>PRA-AI-03 Annual model risk self-assessment to PRA</li></ul></td></tr><tr><td>OVL-EUAIA</td><td>EU AI Act Overlay</td><td>All AI systems placed on the EU market or affecting EU persons</td><td><ul><li>Reg. (EU) 2024/1689</li><li>EU AI Act Annex III §5(b) — credit scoring</li><li>Commission implementing acts 2025-2026</li></ul></td><td><ul><li>EUAIA-AI-01 CE conformity (Art. 43) for high-risk systems</li><li>EUAIA-AI-02 Post-market monitoring (Art. 72) live</li><li>EUAIA-AI-03 Serious incident reporting within 15 days (Art. 73)</li><li>EUAIA-AI-04 Registration in EU database (Art. 49)</li></ul></td></tr><tr><td>OVL-GDPR</td><td>GDPR Overlay</td><td>Any processing of EU personal data</td><td><ul><li>Reg. (EU) 2016/679 Articles 5/6/9/22/25/32/33/34/35</li><li>EDPB Guidelines 03/2022 on AI</li></ul></td><td><ul><li>GDPR-AI-01 Art. 22 safeguards: human review path documented</li><li>GDPR-AI-02 DPIA refreshed on material change</li><li>GDPR-AI-03 Data minimisation tested via leakage probes</li></ul></td></tr></tbody></table></div>
+</div>
+<div class='section' id='M3-S2'>
+<h3>M3-S2 · Overlay precedence &amp; conflict resolution</h3>
+<div class='sub'><h4>rules</h4><ul><li>Strictest applicable provision wins (tier ordering).</li><li>Where overlays diverge on disclosure scope, union of disclosures applies; classification follows the home regulator.</li><li>Conflict log maintained with Legal sign-off for every override.</li></ul></div>
+</div>
+<div class='section' id='M3-S3'>
+<h3>M3-S3 · Mapping matrix snapshot</h3>
+<div class='sub'><h4>matrix</h4><table class='grid'><thead><tr><th>control</th><th>ISO42001</th><th>ECB</th><th>Fed</th><th>PRA</th><th>EUAIA</th><th>GDPR</th></tr></thead><tbody><tr><td>Independent validation</td><td>8.3</td><td>ECB-AI-01/03</td><td>FED-AI-01/02</td><td>PRA-AI-02</td><td>Art. 17 QMS / 43</td><td>—</td></tr><tr><td>Adverse-action explanation</td><td>Annex A 6.2.7</td><td>—</td><td>FCRA §615</td><td>FCA Consumer Duty</td><td>Art. 13/86</td><td>Art. 22</td></tr><tr><td>Post-market monitoring</td><td>9.1</td><td>ECB-AI-02</td><td>FED-AI-03</td><td>PRA-AI-03</td><td>Art. 72</td><td>Art. 35(11)</td></tr><tr><td>Incident reporting</td><td>10.2</td><td>Operational incident framework</td><td>SR 11-7 weakness reporting</td><td>SS1/23 §3.5</td><td>Art. 73</td><td>Art. 33/34</td></tr></tbody></table></div>
+</div>
+</section>
+<section class='module' id='M4'>
+<h2>M4 · M4 — Regulator Submission Packs (RSP v1.0 → v2.6)</h2>
+<p class='summary'>Versioned submission packs evolving from PDF-based static packs to fully machine-readable, signed, decision-traceable bundles.</p>
+<div class='section' id='M4-S1'>
+<h3>M4-S1 · Version roadmap</h3>
+<div class='sub'><h4>versions</h4><table class='grid'><thead><tr><th>id</th><th>year</th><th>format</th><th>scope</th><th>automation</th><th>signing</th></tr></thead><tbody><tr><td>RSP-v1.0</td><td>2026</td><td>PDF + JSON manifest</td><td>Single jurisdiction (home regulator)</td><td>30%</td><td>PGP detached signature</td></tr><tr><td>RSP-v1.5</td><td>2026</td><td>PDF + JSON-LD + Sigstore</td><td>Home + 1 host regulator</td><td>55%</td><td>Sigstore + Rekor transparency log</td></tr><tr><td>RSP-v2.0</td><td>2027</td><td>Structured JSON-LD bundle (machine-readable)</td><td>Multi-jurisdiction (ECB + PRA + Fed)</td><td>75%</td><td>in-toto attestations</td></tr><tr><td>RSP-v2.2</td><td>2027</td><td>JSON-LD + Decision-Traceability API</td><td>Adds GDPR + EU AI Act DB linkage</td><td>85%</td><td>in-toto + Cosign</td></tr><tr><td>RSP-v2.4</td><td>2028</td><td>JSON-LD + live API + OPA-validated policy bundle</td><td>All overlays, federated submission</td><td>92%</td><td>PQC-ready (Dilithium hybrid)</td></tr><tr><td>RSP-v2.5</td><td>2029</td><td>v2.4 + formally-verified obligation graph</td><td>Adds machine-checkable legal logic</td><td>95%</td><td>PQC + Merkle anchored to public ledger</td></tr><tr><td>RSP-v2.6</td><td>2030</td><td>Continuous streaming attestation</td><td>Autonomous-supervisor compatible</td><td>98%</td><td>PQC + FROST threshold + ZK predicates</td></tr></tbody></table></div>
+</div>
+<div class='section' id='M4-S2'>
+<h3>M4-S2 · RSP package structure (v2.4+)</h3>
+<div class='sub'><h4>structure</h4><ul><li>/rsp/manifest.jsonld — top-level bundle</li><li>/rsp/model-card.json</li><li>/rsp/datasheet.json</li><li>/rsp/fria-dpia.json</li><li>/rsp/validation-report.json</li><li>/rsp/monitoring-plan.json</li><li>/rsp/incident-plan.json</li><li>/rsp/decisions/ (signed decision envelopes)</li><li>/rsp/policy-bundle.tar.gz (OPA bundle)</li><li>/rsp/attestations/ (in-toto / Cosign / Rekor)</li><li>/rsp/hash-chain.json (Merkle root + signatures)</li></ul></div>
+</div>
+<div class='section' id='M4-S3'>
+<h3>M4-S3 · Decision-traceability API</h3>
+<div class='sub'><h4>endpoints</h4><ul><li>GET /rsp/{rspId}/decisions/{decisionId} — full reproducible decision</li><li>GET /rsp/{rspId}/decisions?subjectId=… — subject access</li><li>GET /rsp/{rspId}/lineage — model + data lineage graph</li><li>GET /rsp/{rspId}/attestations — verifiable bundle</li><li>POST /rsp/{rspId}/challenge — supervisor counterfactual probe</li></ul></div>
+<div class='sub'><h4>slas</h4><table class='kv'><tr><td class='k'>decisionLookup</td><td class='v'>&lt;= 200 ms p95</td></tr><tr><td class='k'>lineageGraph</td><td class='v'>&lt;= 1 s p95</td></tr><tr><td class='k'>challengeReply</td><td class='v'>&lt;= 5 minutes p95</td></tr></table></div>
+<div class='sub'><h4>auth</h4>mTLS + supervisor SPIFFE ID + per-call OPA policy</div>
+</div>
+<div class='section' id='M4-S4'>
+<h3>M4-S4 · RSP issuance pipeline</h3>
+<div class='sub'><h4>stages</h4><ul><li>Trigger: model promotion / quarterly cadence / supervisor request</li><li>Assemble: pull artefacts from registry, evaluator, monitor</li><li>Validate: OPA policy bundle compliance check</li><li>Sign: in-toto layout + Cosign + Rekor entry</li><li>Publish: regulator portal + internal evidence WORM</li><li>Notify: supervisor + Internal Audit + Board pack</li></ul></div>
+</div>
+</section>
+<section class='module' id='M5'>
+<h2>M5 · M5 — Terraform + OPA Technical Enforcement</h2>
+<p class='summary'>Compliance-as-code substrate enforcing AIMS controls at infrastructure, pipeline, and runtime layers.</p>
+<div class='section' id='M5-S1'>
+<h3>M5-S1 · Terraform modules</h3>
+<div class='sub'><h4>modules</h4><table class='grid'><thead><tr><th>name</th><th>purpose</th></tr></thead><tbody><tr><td>aims-baseline</td><td>VPC/KMS/IAM/WORM-S3/Kafka baseline</td></tr><tr><td>aims-evidence</td><td>Object Lock + Lambda hash-chain anchor</td></tr><tr><td>aims-runtime</td><td>EKS/GKE clusters + admission controllers</td></tr><tr><td>aims-supervisor</td><td>Supervisor mTLS endpoints + SPIFFE</td></tr><tr><td>aims-pqc</td><td>PQC KMS keys + dual-signing CI</td></tr></tbody></table></div>
+</div>
+<div class='section' id='M5-S2'>
+<h3>M5-S2 · OPA policy bundles</h3>
+<div class='sub'><h4>bundles</h4><ul><li>policy/aims-baseline.tar.gz (Annex A controls)</li><li>policy/overlay-ecb.tar.gz</li><li>policy/overlay-fed.tar.gz</li><li>policy/overlay-pra.tar.gz</li><li>policy/overlay-euaia.tar.gz</li><li>policy/overlay-gdpr.tar.gz</li><li>policy/use-case-credit-underwriting.tar.gz</li></ul></div>
+<div class='sub'><h4>decisionPoints</h4><ul><li>Terraform plan (pre-apply) — block insecure infra</li><li>CI gate (pre-merge) — model card + eval coverage</li><li>Admission controller (Kubernetes) — image attestation</li><li>Inference gateway (runtime) — per-call obligations</li><li>Egress filter — prohibited-use checks</li></ul></div>
+</div>
+<div class='section' id='M5-S3'>
+<h3>M5-S3 · Continuous configuration audit</h3>
+<div class='sub'><h4>controls</h4><ul><li>Daily Terraform drift scan with auto-remediation PR</li><li>Hourly OPA bundle integrity check (signed digest)</li><li>Per-region misconfiguration KPI dashboard</li><li>Auto-quarantine of non-compliant workloads</li></ul></div>
+</div>
+</section>
+<section class='module' id='M6'>
+<h2>M6 · M6 — Adversarial &amp; Self-Healing Governance Loops</h2>
+<p class='summary'>Continuous adversarial exercise of both models and controls, paired with auto-remediation that closes the loop without human intervention for known failure modes.</p>
+<div class='section' id='M6-S1'>
+<h3>M6-S1 · Adversarial governance loop</h3>
+<div class='sub'><h4>stages</h4><ul><li>Generate: red-team agents author attacks against models + controls</li><li>Execute: attacks run in sandboxed twin environment</li><li>Detect: monitors flag deltas vs. baseline behavior</li><li>Triage: severity scored against impact taxonomy</li><li>Remediate: control patch / model rollback / policy update</li><li>Attest: signed evidence captured in WORM</li></ul></div>
+<div class='sub'><h4>cadence</h4>Continuous (on-demand + nightly + monthly chaos day)</div>
+</div>
+<div class='section' id='M6-S2'>
+<h3>M6-S2 · Self-healing playbooks</h3>
+<div class='sub'><h4>playbooks</h4><table class='grid'><thead><tr><th>id</th><th>trigger</th><th>action</th><th>humanGate</th></tr></thead><tbody><tr><td>SH-01</td><td>PSI &gt; 0.2 on protected attribute</td><td>Auto-rollback to previous model version + open Sev-2 ticket</td><td>CRO post-hoc review within 24h</td></tr><tr><td>SH-02</td><td>OPA policy bundle digest mismatch</td><td>Quarantine workload + restore last-known-good bundle</td><td>CISO + CCO joint review</td></tr><tr><td>SH-03</td><td>Adverse-action SLA breach predicted</td><td>Failover to deterministic fallback scoring + notify ops</td><td>Head of Credit + DPO</td></tr><tr><td>SH-04</td><td>FRIA risk score escalation</td><td>Block new deployments of system + escalate to Risk Committee</td><td>Board Risk Committee within 5 business days</td></tr></tbody></table></div>
+</div>
+<div class='section' id='M6-S3'>
+<h3>M6-S3 · Adversarial assurance KPIs</h3>
+<div class='sub'><h4>kpis</h4><table class='kv'><tr><td class='k'>redTeamCoverage</td><td class='v'>&gt;= 95% of high-risk systems / quarter</td></tr><tr><td class='k'>novelAttackDiscoveryRate</td><td class='v'>&gt;= 5 net-new attack classes / year</td></tr><tr><td class='k'>selfHealingResolutionRate</td><td class='v'>&gt;= 80% Sev-2 without human action</td></tr><tr><td class='k'>meanTimeToRemediate</td><td class='v'>&lt;= 30 min (Sev-2), &lt;= 4 h (Sev-1)</td></tr></table></div>
+</div>
+</section>
+<section class='module' id='M7'>
+<h2>M7 · M7 — Predictive Governance &amp; Formally-Verified Legal Logic</h2>
+<p class='summary'>Forecast control breaches before they occur and prove obligations are correctly implemented using machine-checkable specifications.</p>
+<div class='section' id='M7-S1'>
+<h3>M7-S1 · Predictive governance</h3>
+<div class='sub'><h4>approach</h4>Treat governance KPIs (PSI, AIR, MTTR, evidence completeness) as time series; forecast breach probability and pre-emptively trigger remediation.</div>
+<div class='sub'><h4>models</h4><ul><li>Drift forecaster (Prophet + ARIMA ensemble) — 7-day horizon</li><li>Fairness drift forecaster — protected-attribute aware</li><li>Control-fatigue forecaster (audit findings as proxy)</li><li>Regulatory-question forecaster (LLM-driven, supervised by Legal)</li></ul></div>
+<div class='sub'><h4>outputs</h4><ul><li>Predicted breaches with calibrated confidence</li><li>Recommended interventions (pre-staged remediation PRs)</li><li>Board pre-warning dashboard (T-30 days)</li></ul></div>
+</div>
+<div class='section' id='M7-S2'>
+<h3>M7-S2 · Formally-verified obligation graph</h3>
+<div class='sub'><h4>approach</h4>Encode regulator obligations as an obligation graph in TLA+/Lean and prove the implementation refines the specification.</div>
+<div class='sub'><h4>specs</h4><ul><li>FCRA §615 adverse-action obligation (Lean spec, mechanically checked)</li><li>GDPR Art. 22 human-review-path obligation (TLA+)</li><li>EU AI Act Art. 73 incident-reporting obligation (TLA+ liveness)</li><li>ECB ICAAP Pillar 2 AI add-on quantification (Lean)</li></ul></div>
+<div class='sub'><h4>deliverable</h4>Each spec ships with a CI job that fails the build if a code change breaks refinement.</div>
+</div>
+<div class='section' id='M7-S3'>
+<h3>M7-S3 · Counterfactual + causal regulator queries</h3>
+<div class='sub'><h4>capability</h4>Supervisors can issue causal queries (&quot;if income were +10%, would the decision flip?&quot;) that the system answers with a causal model + uncertainty, not just correlations.</div>
+<div class='sub'><h4>engines</h4><ul><li>DoWhy + EconML for causal effect estimation</li><li>DiCE / Alibi for actionable counterfactuals</li><li>LiNGAM / NOTEARS for structure discovery (governed)</li></ul></div>
+</div>
+</section>
+<section class='module' id='M8'>
+<h2>M8 · M8 — Cross-Regulator Federation &amp; Autonomous Supervisory Ecosystem</h2>
+<p class='summary'>Federate disclosures across supervisors and prepare for autonomous supervisory ecosystems by 2030.</p>
+<div class='section' id='M8-S1'>
+<h3>M8-S1 · Federation protocol (FedReg)</h3>
+<div class='sub'><h4>transport</h4>mTLS + SPIFFE IDs + OAuth2 Mutual-TLS Client Auth</div>
+<div class='sub'><h4>schema</h4>JSON-LD with shared regulator vocabulary (W3C ODRL extension)</div>
+<div class='sub'><h4>operations</h4><ul><li>Disclose: scoped artefact share with consent metadata</li><li>Subscribe: supervisor receives delta stream</li><li>Challenge: supervisor issues counterfactual / explainability query</li><li>Attest: institution returns signed answer with provenance</li></ul></div>
+<div class='sub'><h4>consentModel</h4>Per-scope, per-purpose, time-bounded, revocable</div>
+</div>
+<div class='section' id='M8-S2'>
+<h3>M8-S2 · Autonomous Supervisory Tiers</h3>
+<div class='sub'><h4>tiers</h4><table class='grid'><thead><tr><th>tier</th><th>name</th><th>year</th><th>description</th></tr></thead><tbody><tr><td>T0</td><td>Manual</td><td>&lt;2026</td><td>PDF + portal uploads</td></tr><tr><td>T1</td><td>Structured</td><td>2026</td><td>Machine-readable RSP, manual review</td></tr><tr><td>T2</td><td>Streaming</td><td>2027-2028</td><td>Continuous attestation feed</td></tr><tr><td>T3</td><td>Federated</td><td>2028-2029</td><td>Cross-regulator query graph</td></tr><tr><td>T4</td><td>Autonomous (advisory)</td><td>2029-2030</td><td>Supervisor AI agents issue advisories</td></tr><tr><td>T5</td><td>Autonomous (binding-with-human-override)</td><td>2030+</td><td>Binding decisions with statutory human override</td></tr></tbody></table></div>
+</div>
+<div class='section' id='M8-S3'>
+<h3>M8-S3 · Privacy &amp; sovereignty controls in federation</h3>
+<div class='sub'><h4>controls</h4><ul><li>Differential privacy on aggregate disclosures (ε &lt;= 1)</li><li>Zero-knowledge predicates for sensitive thresholds</li><li>Data residency tags enforced at egress filter</li><li>Per-jurisdiction key custody with HSM + threshold signing (FROST)</li></ul></div>
+</div>
+<div class='section' id='M8-S4'>
+<h3>M8-S4 · Joint examination workflow</h3>
+<div class='sub'><h4>scenario</h4>ECB + FRB + PRA jointly examine AI-CR-UNDERWRITE-01. Each receives scoped, signed RSP slices; queries federated through FedReg; institution responses attested into a shared transparency log.</div>
+<div class='sub'><h4>sla</h4>Joint final report within 30 calendar days</div>
+</div>
+</section>
+<section class='module' id='M9'>
+<h2>M9 · M9 — High-Risk Credit Underwriting Best-Practice Pattern (AI-CR-UNDERWRITE-01)</h2>
+<p class='summary'>Reference end-to-end pattern for high-risk retail &amp; SME credit underwriting under EU AI Act Annex III §5(b), FCRA, ECOA, and PRA / Fed MRM.</p>
+<div class='section' id='M9-S1'>
+<h3>M9-S1 · Use-case scope &amp; risk classification</h3>
+<div class='sub'><h4>details</h4><table class='kv'><tr><td class='k'>euAiActTier</td><td class='v'>High-risk (Annex III §5(b))</td></tr><tr><td class='k'>internalTier</td><td class='v'>T3 (material consumer impact)</td></tr><tr><td class='k'>modelRiskTier</td><td class='v'>Tier 1</td></tr><tr><td class='k'>regulators</td><td class='v'><ul><li>ECB</li><li>Fed</li><li>PRA</li><li>FCA</li><li>CFPB</li><li>ICO</li><li>EDPB</li></ul></td></tr><tr><td class='k'>decisionVolume</td><td class='v'>~12M decisions / year</td></tr></table></div>
+</div>
+<div class='section' id='M9-S2'>
+<h3>M9-S2 · Data governance</h3>
+<div class='sub'><h4>controls</h4><ul><li>Datasheet (Gebru+) with provenance, sampling, bias notes</li><li>Protected attributes proxied + monitored (no direct use)</li><li>Synthetic counterfactual training augmentation for AIR uplift</li><li>Quarterly representativeness audit by Internal Audit</li></ul></div>
+</div>
+<div class='section' id='M9-S3'>
+<h3>M9-S3 · Model development &amp; validation</h3>
+<div class='sub'><h4>controls</h4><ul><li>Champion/challenger with at least 2 independent architectures</li><li>GBM + monotonic constraints on protected proxies</li><li>Independent 2nd LoD validation (effective challenge)</li><li>FRIA + DPIA refreshed each retrain</li><li>Reproducibility: bit-exact training pipeline pinned</li></ul></div>
+</div>
+<div class='section' id='M9-S4'>
+<h3>M9-S4 · Decisioning &amp; adverse action</h3>
+<div class='sub'><h4>controls</h4><ul><li>Per-decision SHAP + counterfactual stored with envelope</li><li>Adverse-action notice generated within 24h (FCRA §615)</li><li>GDPR Art. 22 human-review path for any decision contested</li><li>EU AI Act Art. 86 right to explanation served via portal</li><li>Decision envelope signed (Ed25519 + PQC dual-sign)</li></ul></div>
+</div>
+<div class='section' id='M9-S5'>
+<h3>M9-S5 · Monitoring &amp; continuous compliance</h3>
+<div class='sub'><h4>controls</h4><ul><li>Drift: PSI per feature + per protected attribute, daily</li><li>Fairness: AIR + EOD + DI ratio, daily</li><li>Stability: KS, ROC-AUC delta vs. baseline, weekly</li><li>Calibration: Brier score, monthly</li><li>Adversarial: prompt-injection / data-poisoning probes, nightly</li></ul></div>
+</div>
+<div class='section' id='M9-S6'>
+<h3>M9-S6 · Regulator engagement</h3>
+<div class='sub'><h4>cadence</h4><ul><li>Quarterly RSP v2.4 issuance to home + host regulators</li><li>Material change notification within 5 business days (ECB-AI-01)</li><li>Annual joint examination drill</li><li>Live decision-traceability API for supervisor on-demand probes</li></ul></div>
+</div>
+</section>
+<section class='module' id='M10'>
+<h2>M10 · M10 — Implementation Roadmap (2026–2030)</h2>
+<p class='summary'>Five-phase, board-tracked program plan with gates and KPIs.</p>
+<div class='section' id='M10-S1'>
+<h3>M10-S1 · Phase plan</h3>
+<div class='sub'><h4>phases</h4><table class='grid'><thead><tr><th>id</th><th>name</th><th>window</th><th>objectives</th><th>exitGate</th></tr></thead><tbody><tr><td>P1</td><td>Foundation</td><td>2026 H1</td><td><ul><li>Adopt ISO/IEC 42001 AIMS Sections 1–5</li><li>Stand up AI System Inventory (Annex J1)</li><li>Issue RSP v1.0 for AI-CR-UNDERWRITE-01</li><li>Launch CAIO office with board mandate</li></ul></td><td>Board approval of AIMS + first RSP filed</td></tr><tr><td>P2</td><td>Industrialise</td><td>2026 H2 – 2027 H1</td><td><ul><li>Deploy Terraform + OPA enforcement substrate</li><li>Roll out SoA (Annex J2) across 100% Tier-1 systems</li><li>Issue RSP v1.5 + v2.0</li><li>Launch adversarial governance loop</li></ul></td><td>&gt;= 75% control automation</td></tr><tr><td>P3</td><td>Federate</td><td>2027 H2 – 2028</td><td><ul><li>RSP v2.2 + v2.4 with multi-regulator scope</li><li>FedReg federation pilot with ECB + PRA + Fed</li><li>Activate self-healing playbooks SH-01..04</li><li>Stand up predictive governance forecasters</li></ul></td><td>Joint ECB+Fed+PRA examination drill passed</td></tr><tr><td>P4</td><td>Verify</td><td>2029</td><td><ul><li>Formally verified obligation graph live for top 5 obligations</li><li>RSP v2.5 with machine-checkable legal logic</li><li>Counterfactual / causal supervisor queries supported</li><li>Autonomous supervisor T2-&gt;T3</li></ul></td><td>Independent assurance from ISO 42001 certification body</td></tr><tr><td>P5</td><td>Autonomous</td><td>2030</td><td><ul><li>RSP v2.6 streaming attestation</li><li>Autonomous supervisor T4 advisory mode active</li><li>Cross-regulator binding-with-override pilot</li><li>PQC + ZK predicates fully deployed</li></ul></td><td>Autonomous advisory disclosures accepted by 8+ supervisors</td></tr></tbody></table></div>
+</div>
+<div class='section' id='M10-S2'>
+<h3>M10-S2 · KPI dashboard</h3>
+<div class='sub'><h4>kpis</h4><table class='grid'><thead><tr><th>id</th><th>name</th><th>target</th></tr></thead><tbody><tr><td>K1</td><td>Time-to-regulator-approved deployment</td><td>&lt;= 14 days</td></tr><tr><td>K2</td><td>RSP generation latency</td><td>&lt;= 30 minutes</td></tr><tr><td>K3</td><td>Decision-traceability coverage</td><td>&gt;= 99.95%</td></tr><tr><td>K4</td><td>Control automation rate</td><td>&gt;= 95%</td></tr><tr><td>K5</td><td>Evidence automation</td><td>&gt;= 96%</td></tr><tr><td>K6</td><td>Fairness AIR floor</td><td>&gt;= 0.85</td></tr><tr><td>K7</td><td>Explainability coverage (high-risk)</td><td>100%</td></tr><tr><td>K8</td><td>Adverse-action SLA</td><td>&lt;= 24h auto</td></tr><tr><td>K9</td><td>Regulator notification SLA</td><td>&lt;= 24h / 72h</td></tr><tr><td>K10</td><td>Model inventory coverage</td><td>100%</td></tr><tr><td>K11</td><td>Policy-drift MTTA</td><td>&lt;= 5 min</td></tr><tr><td>K12</td><td>Self-healing resolution rate</td><td>&gt;= 80% Sev-2</td></tr><tr><td>K13</td><td>Audit finding closure</td><td>&gt;= 95% within SLA</td></tr><tr><td>K14</td><td>Board attestation cadence</td><td>Quarterly + ad-hoc</td></tr><tr><td>K15</td><td>WORM retention</td><td>10 years</td></tr><tr><td>K16</td><td>Federated supervisor count</td><td>&gt;= 8</td></tr></tbody></table></div>
+</div>
+<div class='section' id='M10-S3'>
+<h3>M10-S3 · Top risks &amp; mitigations</h3>
+<div class='sub'><h4>risks</h4><table class='grid'><thead><tr><th>id</th><th>risk</th><th>mitigation</th></tr></thead><tbody><tr><td>R1</td><td>Regulatory divergence post-2027</td><td>Overlay precedence engine + Legal council monthly</td></tr><tr><td>R2</td><td>Supervisor reluctance to accept machine-readable filings</td><td>Dual format (PDF + JSON-LD) until T2</td></tr><tr><td>R3</td><td>Formal verification toolchain immaturity</td><td>Hybrid test-based + spec-based assurance</td></tr><tr><td>R4</td><td>PQC migration breakage</td><td>Hybrid signing + staged rollouts</td></tr><tr><td>R5</td><td>Self-healing causes incident drift</td><td>Human gate on every Sev-1; quarterly chaos drills</td></tr></tbody></table></div>
+</div>
+</section>
+<section class='module' id='M11'>
+<h2>M11 · M11 — Governance Operating Model (3 LoD + RACI)</h2>
+<p class='summary'>Roles, accountabilities, and committee architecture.</p>
+<div class='section' id='M11-S1'>
+<h3>M11-S1 · Three Lines of Defense</h3>
+<div class='sub'><h4>lod</h4><table class='grid'><thead><tr><th>line</th><th>owner</th><th>responsibilities</th></tr></thead><tbody><tr><td>1st LoD</td><td>Business + AI engineering</td><td>Build, operate, monitor models within risk appetite</td></tr><tr><td>2nd LoD</td><td>MRM + Compliance + DPO + CISO</td><td>Independent challenge, validation, policy, oversight</td></tr><tr><td>3rd LoD</td><td>Internal Audit</td><td>Audit AIMS effectiveness; audit the 2nd LoD</td></tr></tbody></table></div>
+</div>
+<div class='section' id='M11-S2'>
+<h3>M11-S2 · RACI matrix (key activities)</h3>
+<div class='sub'><h4>matrix</h4><table class='grid'><thead><tr><th>activity</th><th>Board</th><th>CEO</th><th>CRO</th><th>CCO</th><th>CAIO</th><th>DPO</th><th>CISO</th><th>InternalAudit</th></tr></thead><tbody><tr><td>Approve AI Policy</td><td>A</td><td>R</td><td>C</td><td>C</td><td>C</td><td>I</td><td></td><td></td></tr><tr><td>Approve Tier-1 model</td><td>I</td><td>I</td><td>A</td><td>C</td><td>R</td><td>C</td><td></td><td></td></tr><tr><td>Issue RSP</td><td>I</td><td>I</td><td>A</td><td>R</td><td>R</td><td>C</td><td></td><td></td></tr><tr><td>Sev-1 incident response</td><td>I</td><td>I</td><td>A</td><td>C</td><td>R</td><td>C</td><td>R</td><td></td></tr><tr><td>Annual AIMS audit</td><td>I</td><td>I</td><td>C</td><td>C</td><td>C</td><td>C</td><td></td><td>AR</td></tr></tbody></table></div>
+</div>
+<div class='section' id='M11-S3'>
+<h3>M11-S3 · Committee architecture</h3>
+<div class='sub'><h4>committees</h4><table class='grid'><thead><tr><th>id</th><th>name</th><th>frequency</th><th>chair</th></tr></thead><tbody><tr><td>C1</td><td>Board AI Oversight Committee</td><td>Quarterly</td><td>Independent NED</td></tr><tr><td>C2</td><td>Group AI Risk Committee</td><td>Monthly</td><td>CRO</td></tr><tr><td>C3</td><td>Model Approval Committee</td><td>Bi-weekly</td><td>CAIO</td></tr><tr><td>C4</td><td>AI Ethics Council</td><td>Monthly</td><td>GC + external ethicist</td></tr><tr><td>C5</td><td>Regulator Engagement Forum</td><td>Monthly</td><td>CCO</td></tr></tbody></table></div>
+</div>
+</section>
+<section class='module' id='M12'>
+<h2>M12 · M12 — Reporting &amp; Disclosure Templates</h2>
+<p class='summary'>Standardised, machine-readable templates for every audience.</p>
+<div class='section' id='M12-S1'>
+<h3>M12-S1 · Audience matrix</h3>
+<div class='sub'><h4>matrix</h4><table class='grid'><thead><tr><th>audience</th><th>report</th><th>format</th></tr></thead><tbody><tr><td>Board</td><td>Quarterly AI Risk &amp; KPI Pack</td><td>PDF + JSON-LD</td></tr><tr><td>Regulator (home)</td><td>RSP v2.4+</td><td>JSON-LD bundle + signatures</td></tr><tr><td>Regulator (host)</td><td>Federated RSP slice</td><td>FedReg streaming</td></tr><tr><td>Customer (adverse action)</td><td>Adverse-action notice + explanation</td><td>Multilingual portal + paper</td></tr><tr><td>Internal Audit</td><td>AIMS audit dossier</td><td>Evidence bundle + Merkle root</td></tr><tr><td>Public</td><td>Transparency report</td><td>PDF + W3C transparency log link</td></tr></tbody></table></div>
+</div>
+<div class='section' id='M12-S2'>
+<h3>M12-S2 · Markdown template skeleton</h3>
+<div class='sub'><h4>tags</h4><ul><li>&lt;title&gt;</li><li>&lt;abstract&gt;</li><li>&lt;content&gt;</li></ul></div>
+<div class='sub'><h4>skeleton</h4>&lt;title&gt;Quarterly AI Risk &amp; KPI Pack — 2026 Q4&lt;/title&gt;
+&lt;abstract&gt;Summary of KPI movement, top risks, and regulator interactions for the quarter.&lt;/abstract&gt;
+&lt;content&gt;1. KPI dashboard (K1..K16)
+2. Material model changes
+3. Incidents (Sev-0..Sev-2)
+4. Regulator engagements (RSP issuances, queries)
+5. Internal Audit findings status
+6. Forward-looking risks (predictive governance)
+7. Board decisions requested&lt;/content&gt;</div>
+</div>
+<div class='section' id='M12-S3'>
+<h3>M12-S3 · Disclosure principles</h3>
+<div class='sub'><h4>principles</h4><ul><li>Truthful, complete, and timely</li><li>Audience-fit (no jargon to customers; rigour to supervisors)</li><li>Verifiable (every claim traceable to a signed evidence record)</li><li>Privacy-preserving (DP / ZK on aggregate disclosures)</li></ul></div>
+</div>
+</section>
+
+  <section class="module" id="regulatory">
+    <h2>Regulatory Alignment</h2>
+    <ul><li>ISO/IEC 42001:2023 — AI Management System (AIMS) — primary anchor</li><li>ISO/IEC 23894:2023 — AI Risk Management</li><li>ISO/IEC 5338:2023 — AI System Life Cycle Processes</li><li>ISO/IEC 27001:2022 / 27701:2019 / 27018:2019</li><li>ISO/IEC TR 24028 / 24029 / 24368 (trustworthiness)</li><li>EU AI Act (Reg. (EU) 2024/1689) — Art. 6, 9, 10, 12, 13, 14, 15, 17, 26, 27, 49, 53, 55, 72, 73; Annex III §5(b)</li><li>GDPR (Reg. (EU) 2016/679) — Art. 5, 6, 9, 22, 25, 32, 33, 34, 35</li><li>ECB SSM Guide on internal models (2024) + Targeted Review of Internal Models (TRIM) AI extensions</li><li>Federal Reserve SR 11-7 / OCC 2011-12 — Model Risk Management</li><li>PRA SS1/23 — Model Risk Management Principles for Banks (UK)</li><li>PRA SS2/21 — Outsourcing &amp; third-party risk management</li><li>FCA Consumer Duty (PS22/9) + AI/ML discussion paper DP5/22</li><li>Basel III/IV — CRR3 / CRD6 — ICAAP Pillar 2 AI add-on</li><li>FCRA (US) §604/§615 + ECOA / Reg B §1002 (adverse action)</li><li>CFPB Circular 2023-03 (algorithmic adverse-action notices)</li><li>NIST AI RMF 1.0 + GenAI Profile (AI 600-1)</li><li>OECD AI Principles + G7 Hiroshima AI Process Code of Conduct</li><li>Council of Europe Framework Convention on AI (2024)</li><li>OWASP LLM Top 10 (2025) / MITRE ATLAS</li><li>SLSA L3 + Sigstore/Cosign + in-toto attestations</li></ul>
+  </section>
+
+  <section class="module" id="schemas">
+    <h2>JSON Schemas</h2>
+    <p class="summary">8 schemas: AI System Inventory, RSP Manifest, Decision Envelope, Control Mapping, FRIA, Incident Record, FedReg Message, Obligation Spec.</p>
+    <details><summary>aiSystemInventoryEntry</summary><pre><code>{
+  &quot;title&quot;: &quot;AI System Inventory Entry (Annex J1)&quot;,
+  &quot;required&quot;: [
+    &quot;systemId&quot;,
+    &quot;businessOwner&quot;,
+    &quot;euAiActTier&quot;,
+    &quot;internalTier&quot;,
+    &quot;modelRiskTier&quot;,
+    &quot;lastFRIA&quot;,
+    &quot;rspVersion&quot;
+  ],
+  &quot;fields&quot;: {
+    &quot;systemId&quot;: &quot;string&quot;,
+    &quot;businessOwner&quot;: &quot;string&quot;,
+    &quot;euAiActTier&quot;: &quot;enum[Prohibited|HighRisk|Limited|Minimal]&quot;,
+    &quot;internalTier&quot;: &quot;enum[T0|T1|T2|T3|T4|T5]&quot;,
+    &quot;modelRiskTier&quot;: &quot;enum[Tier-1|Tier-2|Tier-3]&quot;,
+    &quot;annexIIIRef&quot;: &quot;string&quot;,
+    &quot;lastFRIA&quot;: &quot;ISO-8601&quot;,
+    &quot;lastDPIA&quot;: &quot;ISO-8601&quot;,
+    &quot;rspVersion&quot;: &quot;string&quot;,
+    &quot;regulatorEngagementStatus&quot;: &quot;enum[Filed|Pending|UnderReview|Approved|Withdrawn]&quot;
+  }
+}</code></pre></details><details><summary>rspManifest</summary><pre><code>{
+  &quot;title&quot;: &quot;Regulator Submission Pack \u2014 Manifest (v2.4+)&quot;,
+  &quot;required&quot;: [
+    &quot;rspId&quot;,
+    &quot;version&quot;,
+    &quot;subjectSystemId&quot;,
+    &quot;issuedAt&quot;,
+    &quot;signatures&quot;,
+    &quot;merkleRoot&quot;
+  ],
+  &quot;fields&quot;: {
+    &quot;rspId&quot;: &quot;string&quot;,
+    &quot;version&quot;: &quot;string&quot;,
+    &quot;subjectSystemId&quot;: &quot;string&quot;,
+    &quot;issuedAt&quot;: &quot;ISO-8601&quot;,
+    &quot;regulators&quot;: &quot;string[]&quot;,
+    &quot;artefacts&quot;: &quot;object[]&quot;,
+    &quot;signatures&quot;: &quot;object[]&quot;,
+    &quot;merkleRoot&quot;: &quot;hex&quot;,
+    &quot;policyBundleDigest&quot;: &quot;hex&quot;,
+    &quot;ledgerAnchorTx&quot;: &quot;string&quot;
+  }
+}</code></pre></details><details><summary>decisionEnvelope</summary><pre><code>{
+  &quot;title&quot;: &quot;Decision Envelope (per AI decision)&quot;,
+  &quot;required&quot;: [
+    &quot;decisionId&quot;,
+    &quot;subjectId&quot;,
+    &quot;modelId&quot;,
+    &quot;modelVersion&quot;,
+    &quot;inputsHash&quot;,
+    &quot;output&quot;,
+    &quot;shapTopK&quot;,
+    &quot;ts&quot;,
+    &quot;signature&quot;
+  ],
+  &quot;fields&quot;: {
+    &quot;decisionId&quot;: &quot;string&quot;,
+    &quot;subjectId&quot;: &quot;string&quot;,
+    &quot;modelId&quot;: &quot;string&quot;,
+    &quot;modelVersion&quot;: &quot;string&quot;,
+    &quot;inputsHash&quot;: &quot;hex&quot;,
+    &quot;output&quot;: &quot;object&quot;,
+    &quot;shapTopK&quot;: &quot;object[]&quot;,
+    &quot;counterfactual&quot;: &quot;object&quot;,
+    &quot;policyDecision&quot;: &quot;object&quot;,
+    &quot;ts&quot;: &quot;ISO-8601&quot;,
+    &quot;signature&quot;: &quot;object&quot;
+  }
+}</code></pre></details><details><summary>controlMapping</summary><pre><code>{
+  &quot;title&quot;: &quot;Control Mapping (Annex J2 SoA)&quot;,
+  &quot;required&quot;: [
+    &quot;controlId&quot;,
+    &quot;category&quot;,
+    &quot;iso42001Ref&quot;,
+    &quot;overlays&quot;,
+    &quot;enforcement&quot;
+  ],
+  &quot;fields&quot;: {
+    &quot;controlId&quot;: &quot;string&quot;,
+    &quot;category&quot;: &quot;string&quot;,
+    &quot;iso42001Ref&quot;: &quot;string&quot;,
+    &quot;overlays&quot;: &quot;object&quot;,
+    &quot;enforcement&quot;: &quot;object&quot;,
+    &quot;evidenceAutomation&quot;: &quot;enum[None|Partial|Full]&quot;,
+    &quot;owner&quot;: &quot;string&quot;
+  }
+}</code></pre></details><details><summary>friaRecord</summary><pre><code>{
+  &quot;title&quot;: &quot;FRIA + DPIA Combined Record (Annex J3)&quot;,
+  &quot;required&quot;: [
+    &quot;friaId&quot;,
+    &quot;subjectSystemId&quot;,
+    &quot;phase&quot;,
+    &quot;residualRisk&quot;,
+    &quot;approvers&quot;
+  ],
+  &quot;fields&quot;: {
+    &quot;friaId&quot;: &quot;string&quot;,
+    &quot;subjectSystemId&quot;: &quot;string&quot;,
+    &quot;phase&quot;: &quot;enum[A|B|C|D|E|F]&quot;,
+    &quot;axes&quot;: &quot;object[]&quot;,
+    &quot;residualRisk&quot;: &quot;enum[Low|Medium|High|Critical]&quot;,
+    &quot;approvers&quot;: &quot;string[]&quot;,
+    &quot;nextReviewAt&quot;: &quot;ISO-8601&quot;
+  }
+}</code></pre></details><details><summary>incidentRecord</summary><pre><code>{
+  &quot;title&quot;: &quot;AI Incident Record (Cl. 10.2 + EU AI Act Art. 73)&quot;,
+  &quot;required&quot;: [
+    &quot;incidentId&quot;,
+    &quot;severity&quot;,
+    &quot;detectedAt&quot;,
+    &quot;affectedSystems&quot;,
+    &quot;narrative&quot;
+  ],
+  &quot;fields&quot;: {
+    &quot;incidentId&quot;: &quot;string&quot;,
+    &quot;severity&quot;: &quot;enum[Sev-0|Sev-1|Sev-2|Sev-3]&quot;,
+    &quot;detectedAt&quot;: &quot;ISO-8601&quot;,
+    &quot;affectedSystems&quot;: &quot;string[]&quot;,
+    &quot;regulatorNotifications&quot;: &quot;object[]&quot;,
+    &quot;narrative&quot;: &quot;string&quot;,
+    &quot;rootCause&quot;: &quot;string&quot;,
+    &quot;capa&quot;: &quot;object[]&quot;
+  }
+}</code></pre></details><details><summary>fedRegMessage</summary><pre><code>{
+  &quot;title&quot;: &quot;Federation Protocol Message (FedReg)&quot;,
+  &quot;required&quot;: [
+    &quot;messageId&quot;,
+    &quot;fromSpiffeId&quot;,
+    &quot;toSpiffeId&quot;,
+    &quot;op&quot;,
+    &quot;payloadRef&quot;,
+    &quot;consentScope&quot;
+  ],
+  &quot;fields&quot;: {
+    &quot;messageId&quot;: &quot;string&quot;,
+    &quot;fromSpiffeId&quot;: &quot;string&quot;,
+    &quot;toSpiffeId&quot;: &quot;string&quot;,
+    &quot;op&quot;: &quot;enum[Disclose|Subscribe|Challenge|Attest]&quot;,
+    &quot;payloadRef&quot;: &quot;string&quot;,
+    &quot;consentScope&quot;: &quot;object&quot;,
+    &quot;signatures&quot;: &quot;object[]&quot;,
+    &quot;ts&quot;: &quot;ISO-8601&quot;
+  }
+}</code></pre></details><details><summary>obligationSpec</summary><pre><code>{
+  &quot;title&quot;: &quot;Formally-Verified Obligation Spec&quot;,
+  &quot;required&quot;: [
+    &quot;obligationId&quot;,
+    &quot;regulatorRef&quot;,
+    &quot;specLanguage&quot;,
+    &quot;specHash&quot;,
+    &quot;refinementProof&quot;
+  ],
+  &quot;fields&quot;: {
+    &quot;obligationId&quot;: &quot;string&quot;,
+    &quot;regulatorRef&quot;: &quot;string&quot;,
+    &quot;specLanguage&quot;: &quot;enum[TLA+|Lean|Coq]&quot;,
+    &quot;specHash&quot;: &quot;hex&quot;,
+    &quot;refinementProof&quot;: &quot;string&quot;,
+    &quot;ciJobRef&quot;: &quot;string&quot;
+  }
+}</code></pre></details>
+  </section>
+
+  <section class="module" id="code-examples">
+    <h2>Code Examples</h2>
+    <p class="summary">11 reference implementations: OPA RSP gate, Terraform WORM evidence, decision envelope signer (Ed25519 + PQC), fairness monitor, FedReg client, predictive drift forecaster, TLA+ obligation spec, Lean FCRA spec, self-healing playbook engine, FastAPI traceability API, Merkle anchor.</p>
+    <details><summary>opaRspGate</summary><div class='code-meta'><span class='lang'>rego</span> · <span class='purpose'>Block RSP issuance unless all required artefacts + signatures present</span></div><pre><code>package rsp.gate
+
+default allow = false
+
+required := {&quot;manifest&quot;, &quot;model-card&quot;, &quot;datasheet&quot;, &quot;fria-dpia&quot;,
+             &quot;validation-report&quot;, &quot;monitoring-plan&quot;, &quot;incident-plan&quot;,
+             &quot;policy-bundle&quot;, &quot;attestations&quot;, &quot;hash-chain&quot;}
+
+allow {
+    have := {a | a := input.artefacts[_].name}
+    missing := required - have
+    count(missing) == 0
+    input.signatures.cosign.verified == true
+    input.signatures.intoto.verified == true
+    input.policyBundleDigest == data.policy.expectedDigest
+}
+</code></pre></details><details><summary>terraformWormEvidence</summary><div class='code-meta'><span class='lang'>hcl</span> · <span class='purpose'>S3 Object Lock + KMS WORM evidence bucket (10-year retention)</span></div><pre><code>resource &quot;aws_s3_bucket&quot; &quot;aims_evidence&quot; {
+  bucket = &quot;gsifi-aims-evidence-${var.env}&quot;
+  object_lock_enabled = true
+}
+
+resource &quot;aws_s3_bucket_object_lock_configuration&quot; &quot;lock&quot; {
+  bucket = aws_s3_bucket.aims_evidence.id
+  rule {
+    default_retention {
+      mode = &quot;COMPLIANCE&quot;
+      years = 10
+    }
+  }
+}
+
+resource &quot;aws_s3_bucket_server_side_encryption_configuration&quot; &quot;sse&quot; {
+  bucket = aws_s3_bucket.aims_evidence.id
+  rule {
+    apply_server_side_encryption_by_default {
+      kms_master_key_id = aws_kms_key.aims.arn
+      sse_algorithm     = &quot;aws:kms&quot;
+    }
+  }
+}
+</code></pre></details><details><summary>decisionEnvelopeSigner</summary><div class='code-meta'><span class='lang'>python</span> · <span class='purpose'>Sign per-decision envelopes (Ed25519 + PQC dual-sign)</span></div><pre><code>import hashlib, json, time
+from cryptography.hazmat.primitives.asymmetric.ed25519 import Ed25519PrivateKey
+# pqcrypto.sign.dilithium3 illustrative
+from pqcrypto.sign.dilithium3 import generate_keypair, sign as pqc_sign
+
+def make_envelope(decision_id, subject_id, model_id, model_version,
+                  inputs, output, shap_topk, ed_sk, pqc_sk):
+    inputs_hash = hashlib.sha256(json.dumps(inputs, sort_keys=True).encode()).hexdigest()
+    body = {
+        &quot;decisionId&quot;: decision_id,
+        &quot;subjectId&quot;: subject_id,
+        &quot;modelId&quot;: model_id,
+        &quot;modelVersion&quot;: model_version,
+        &quot;inputsHash&quot;: inputs_hash,
+        &quot;output&quot;: output,
+        &quot;shapTopK&quot;: shap_topk,
+        &quot;ts&quot;: time.strftime(&quot;%Y-%m-%dT%H:%M:%SZ&quot;, time.gmtime()),
+    }
+    payload = json.dumps(body, sort_keys=True).encode()
+    sig_ed = ed_sk.sign(payload).hex()
+    sig_pqc = pqc_sign(pqc_sk, payload).hex()
+    body[&quot;signature&quot;] = {&quot;ed25519&quot;: sig_ed, &quot;dilithium3&quot;: sig_pqc}
+    return body
+</code></pre></details><details><summary>fairnessMonitor</summary><div class='code-meta'><span class='lang'>python</span> · <span class='purpose'>Daily AIR / EOD monitor with self-healing trigger (SH-01)</span></div><pre><code>import numpy as np
+
+def adverse_impact_ratio(y_pred, protected):
+    rates = {g: y_pred[protected == g].mean() for g in np.unique(protected)}
+    ref = max(rates.values())
+    return min(rates.values()) / ref if ref else 1.0
+
+def monitor(daily_predictions, protected, prev_air, prev_psi):
+    air = adverse_impact_ratio(daily_predictions, protected)
+    if air &lt; 0.85 or prev_psi &gt; 0.2:
+        trigger_self_heal(&quot;SH-01&quot;, reason={&quot;air&quot;: air, &quot;psi&quot;: prev_psi})
+    return {&quot;air&quot;: air}
+
+def trigger_self_heal(playbook_id, reason):
+    # POST signed event to governance bus → triggers rollback + Sev-2 ticket
+    ...
+</code></pre></details><details><summary>fedRegClient</summary><div class='code-meta'><span class='lang'>python</span> · <span class='purpose'>FedReg federation client — disclose RSP slice to supervisor</span></div><pre><code>import requests, json, time
+
+def disclose(supervisor_url, rsp_slice, scope, spiffe_ctx, signer):
+    msg = {
+        &quot;messageId&quot;: f&quot;msg-{int(time.time()*1000)}&quot;,
+        &quot;fromSpiffeId&quot;: spiffe_ctx.self_id,
+        &quot;toSpiffeId&quot;:   spiffe_ctx.peer_id,
+        &quot;op&quot;: &quot;Disclose&quot;,
+        &quot;payloadRef&quot;: rsp_slice[&quot;uri&quot;],
+        &quot;consentScope&quot;: scope,
+        &quot;ts&quot;: time.strftime(&quot;%Y-%m-%dT%H:%M:%SZ&quot;, time.gmtime()),
+    }
+    body = json.dumps(msg, sort_keys=True).encode()
+    msg[&quot;signatures&quot;] = signer(body)
+    return requests.post(supervisor_url + &quot;/fedreg/v1/messages&quot;,
+                         json=msg, cert=spiffe_ctx.mtls_cert).json()
+</code></pre></details><details><summary>predictiveDriftForecaster</summary><div class='code-meta'><span class='lang'>python</span> · <span class='purpose'>Forecast PSI breach 7 days ahead (predictive governance)</span></div><pre><code>from prophet import Prophet
+import pandas as pd
+
+def forecast_psi_breach(history_df, threshold=0.2, horizon=7):
+    m = Prophet(interval_width=0.95).fit(history_df.rename(columns={&quot;date&quot;:&quot;ds&quot;,&quot;psi&quot;:&quot;y&quot;}))
+    future = m.make_future_dataframe(periods=horizon)
+    fcst = m.predict(future)
+    breach = fcst[fcst[&quot;yhat&quot;] &gt; threshold].head(1)
+    return None if breach.empty else {
+        &quot;predictedBreachAt&quot;: str(breach.iloc[0][&quot;ds&quot;].date()),
+        &quot;expectedPsi&quot;: float(breach.iloc[0][&quot;yhat&quot;]),
+    }
+</code></pre></details><details><summary>tlaPlusObligation</summary><div class='code-meta'><span class='lang'>tla</span> · <span class='purpose'>TLA+ liveness spec for EU AI Act Art. 73 incident reporting</span></div><pre><code>-------------- MODULE Art73Reporting --------------
+EXTENDS Naturals, TLC
+VARIABLES status, notifiedAt, detectedAt
+Init == /\ status = &quot;open&quot; /\ notifiedAt = 0 /\ detectedAt = 0
+Report == /\ status = &quot;open&quot; /\ status&#x27; = &quot;reported&quot;
+          /\ notifiedAt&#x27; = detectedAt + 15
+Liveness == &lt;&gt;(status = &quot;reported&quot; /\ notifiedAt - detectedAt &lt;= 15)
+Spec == Init /\ [][Report]_&lt;&lt;status, notifiedAt, detectedAt&gt;&gt; /\ Liveness
+====
+</code></pre></details><details><summary>leanFcraSpec</summary><div class='code-meta'><span class='lang'>lean</span> · <span class='purpose'>Lean spec for FCRA §615 adverse-action obligation</span></div><pre><code>import data.real.basic
+
+structure Decision := (subject : string) (denied : bool) (timestamp_h : nat)
+structure Notice   := (subject : string) (sent_at_h : nat) (reasons : list string)
+
+def fcra_compliant (d : Decision) (n : Notice) : Prop :=
+  d.subject = n.subject
+  ∧ d.denied = tt
+  ∧ n.sent_at_h ≤ d.timestamp_h + 30 * 24
+  ∧ n.reasons.length ≥ 1
+
+theorem fcra_demo :
+  ∀ d n, d.denied = tt → fcra_compliant d n → n.reasons.length ≥ 1 :=
+λ d n h1 hc, hc.2.2.2
+</code></pre></details><details><summary>selfHealingPlaybookEngine</summary><div class='code-meta'><span class='lang'>python</span> · <span class='purpose'>Self-healing playbook executor with WORM-attested actions</span></div><pre><code>import json, time, hashlib
+
+def execute_playbook(playbook, signals, signer, worm_writer):
+    record = {&quot;playbook&quot;: playbook[&quot;id&quot;], &quot;trigger&quot;: playbook[&quot;trigger&quot;],
+              &quot;signals&quot;: signals, &quot;ts&quot;: time.strftime(&quot;%Y-%m-%dT%H:%M:%SZ&quot;)}
+    if playbook[&quot;id&quot;] == &quot;SH-01&quot;:
+        rollback_model(signals[&quot;modelId&quot;])
+        open_ticket(severity=&quot;Sev-2&quot;, reason=&quot;Bias drift&quot;)
+    elif playbook[&quot;id&quot;] == &quot;SH-02&quot;:
+        quarantine_workload(signals[&quot;workloadId&quot;])
+        restore_lkg_bundle()
+    payload = json.dumps(record, sort_keys=True).encode()
+    record[&quot;digest&quot;] = hashlib.sha256(payload).hexdigest()
+    record[&quot;signature&quot;] = signer(payload)
+    worm_writer.write(record)
+    return record
+
+def rollback_model(*a, **k): ...
+def open_ticket(*a, **k): ...
+def quarantine_workload(*a, **k): ...
+def restore_lkg_bundle(*a, **k): ...
+</code></pre></details><details><summary>rspApiFastapi</summary><div class='code-meta'><span class='lang'>python</span> · <span class='purpose'>FastAPI decision-traceability API for RSP v2.4+</span></div><pre><code>from fastapi import FastAPI, HTTPException, Depends
+app = FastAPI(title=&quot;RSP Decision Traceability API&quot;)
+
+def auth(spiffe_id: str = &quot;&quot;): 
+    if not spiffe_id.startswith(&quot;spiffe://supervisor.&quot;):
+        raise HTTPException(401, &quot;Supervisor SPIFFE required&quot;)
+    return spiffe_id
+
+@app.get(&quot;/rsp/{rsp_id}/decisions/{decision_id}&quot;)
+def get_decision(rsp_id: str, decision_id: str, who=Depends(auth)):
+    env = decision_store.fetch(rsp_id, decision_id)
+    if not env: raise HTTPException(404, &quot;Decision not found&quot;)
+    return env
+
+@app.post(&quot;/rsp/{rsp_id}/challenge&quot;)
+def challenge(rsp_id: str, body: dict, who=Depends(auth)):
+    return counterfactual_engine.run(rsp_id, body)
+</code></pre></details><details><summary>merkleAnchor</summary><div class='code-meta'><span class='lang'>python</span> · <span class='purpose'>Daily Merkle anchor of evidence WORM into public ledger</span></div><pre><code>import hashlib
+
+def merkle_root(leaves):
+    layer = [bytes.fromhex(l) for l in leaves]
+    while len(layer) &gt; 1:
+        if len(layer) % 2: layer.append(layer[-1])
+        layer = [hashlib.sha256(layer[i]+layer[i+1]).digest() for i in range(0,len(layer),2)]
+    return layer[0].hex()
+
+def anchor_today(evidence_hashes, ledger_client):
+    root = merkle_root(evidence_hashes)
+    txid = ledger_client.publish(root)
+    return {&quot;root&quot;: root, &quot;txid&quot;: txid, &quot;count&quot;: len(evidence_hashes)}
+</code></pre></details>
+  </section>
+
+  <section class="module" id="case-studies">
+    <h2>Case Studies</h2>
+    <p class="summary">5 reference deployments: EU G-SIB dual ISO/EU AI Act certification, US BHC federated SR 11-7+EU AI Act, UK PRA SS1/23 SMF24 attestation, joint ECB+Fed+PRA examination, self-healing bias drift auto-rollback.</p>
+    <div class='case'><h3>CS-01 · European G-SIB — first ISO/IEC 42001 + EU AI Act dual certification</h3><p><strong>Sector:</strong> Banking (EU)</p><p>Top-3 EU bank achieved ISO/IEC 42001 certification and EU AI Act Art. 43 conformity for AI-CR-UNDERWRITE-01 concurrently.</p><div class='sub'><h4>Outcomes</h4><table class='kv'><tr><td class='k'>rspVersion</td><td class='v'>v2.4</td></tr><tr><td class='k'>regulators</td><td class='v'><ul><li>ECB</li><li>BaFin</li><li>ACPR</li><li>EDPB</li></ul></td></tr><tr><td class='k'>controlAutomation</td><td class='v'>94%</td></tr><tr><td class='k'>auditFindingsCriticalHigh</td><td class='v'>0</td></tr></table></div></div><div class='case'><h3>CS-02 · US BHC — federated SR 11-7 + EU AI Act submission</h3><p><strong>Sector:</strong> Banking (US/EU)</p><p>US bank holding company served SR 11-7 + EU AI Act overlays from a single AIMS, federated to FRB + ECB via FedReg.</p><div class='sub'><h4>Outcomes</h4><table class='kv'><tr><td class='k'>rspVersion</td><td class='v'>v2.2 → v2.4</td></tr><tr><td class='k'>supervisorCount</td><td class='v'>5</td></tr><tr><td class='k'>decisionTraceability</td><td class='v'>99.97%</td></tr><tr><td class='k'>boardAttestation</td><td class='v'>Quarterly + ad-hoc</td></tr></table></div></div><div class='case'><h3>CS-03 · UK firm — PRA SS1/23 SMF24 attestation pipeline</h3><p><strong>Sector:</strong> Banking (UK)</p><p>PRA-authorised firm built an SMF24 senior-manager attestation pipeline auto-generated from AIMS evidence.</p><div class='sub'><h4>Outcomes</h4><table class='kv'><tr><td class='k'>smf24AttestationLatency</td><td class='v'>&lt;= 24h</td></tr><tr><td class='k'>evidenceAutomation</td><td class='v'>97%</td></tr><tr><td class='k'>annualSelfAssessment</td><td class='v'>Filed 11 days early</td></tr></table></div></div><div class='case'><h3>CS-04 · Joint examination drill — ECB + Fed + PRA</h3><p><strong>Sector:</strong> Cross-jurisdiction</p><p>Three home/host supervisors ran a joint examination of AI-CR-UNDERWRITE-01 using FedReg, with binding-with-override advisory issued by an autonomous supervisor agent (T4).</p><div class='sub'><h4>Outcomes</h4><table class='kv'><tr><td class='k'>totalQueries</td><td class='v'>412</td></tr><tr><td class='k'>averageReplyLatency</td><td class='v'>27 minutes</td></tr><tr><td class='k'>challengePassRate</td><td class='v'>98.5%</td></tr><tr><td class='k'>finalReportTime</td><td class='v'>23 days</td></tr></table></div></div><div class='case'><h3>CS-05 · Self-healing in production — bias drift auto-rollback</h3><p><strong>Sector:</strong> Banking</p><p>AIR fell to 0.81 on a protected attribute; SH-01 auto-rolled back the model within 4 minutes, opened Sev-2, and filed a customer-impact pre-warning to Internal Audit.</p><div class='sub'><h4>Outcomes</h4><table class='kv'><tr><td class='k'>detectionToRollback</td><td class='v'>4 min</td></tr><tr><td class='k'>customerImpact</td><td class='v'>0 wrongful denials</td></tr><tr><td class='k'>regulatorNotified</td><td class='v'>ECB + ICO within 6h</td></tr><tr><td class='k'>rcaPublished</td><td class='v'>&lt;= 5 business days</td></tr></table></div></div>
+  </section>
+
+  <section class="module" id="api">
+    <h2>API Endpoints</h2>
+    <p class="summary">Prefix: <code>/api/gsifi-aims</code> · Total planned: 78</p>
+    <ul><li><code>/api/gsifi-aims</code></li><li><code>/api/gsifi-aims/meta</code></li><li><code>/api/gsifi-aims/executive-summary</code></li><li><code>/api/gsifi-aims/summary</code></li><li><code>/api/gsifi-aims/aims</code></li><li><code>/api/gsifi-aims/aims/sections</code></li><li><code>/api/gsifi-aims/aims/sections/:id</code></li><li><code>/api/gsifi-aims/aims/annexes</code></li><li><code>/api/gsifi-aims/aims/annexes/:id</code></li><li><code>/api/gsifi-aims/regulatory</code></li><li><code>/api/gsifi-aims/regulatory/overlays</code></li><li><code>/api/gsifi-aims/regulatory/overlays/:id</code></li><li><code>/api/gsifi-aims/regulatory/precedence</code></li><li><code>/api/gsifi-aims/regulatory/matrix</code></li><li><code>/api/gsifi-aims/rsp</code></li><li><code>/api/gsifi-aims/rsp/versions</code></li><li><code>/api/gsifi-aims/rsp/versions/:id</code></li><li><code>/api/gsifi-aims/rsp/structure</code></li><li><code>/api/gsifi-aims/rsp/api</code></li><li><code>/api/gsifi-aims/rsp/pipeline</code></li><li><code>/api/gsifi-aims/enforcement</code></li><li><code>/api/gsifi-aims/enforcement/terraform</code></li><li><code>/api/gsifi-aims/enforcement/opa</code></li><li><code>/api/gsifi-aims/enforcement/audit</code></li><li><code>/api/gsifi-aims/adversarial</code></li><li><code>/api/gsifi-aims/adversarial/loop</code></li><li><code>/api/gsifi-aims/adversarial/playbooks</code></li><li><code>/api/gsifi-aims/adversarial/kpis</code></li><li><code>/api/gsifi-aims/predictive</code></li><li><code>/api/gsifi-aims/predictive/forecasters</code></li><li><code>/api/gsifi-aims/predictive/formal</code></li><li><code>/api/gsifi-aims/predictive/causal</code></li><li><code>/api/gsifi-aims/federation</code></li><li><code>/api/gsifi-aims/federation/protocol</code></li><li><code>/api/gsifi-aims/federation/tiers</code></li><li><code>/api/gsifi-aims/federation/privacy</code></li><li><code>/api/gsifi-aims/federation/joint-exam</code></li><li><code>/api/gsifi-aims/credit-underwriting</code></li><li><code>/api/gsifi-aims/credit-underwriting/scope</code></li><li><code>/api/gsifi-aims/credit-underwriting/data</code></li><li><code>/api/gsifi-aims/credit-underwriting/dev-validation</code></li><li><code>/api/gsifi-aims/credit-underwriting/decisioning</code></li><li><code>/api/gsifi-aims/credit-underwriting/monitoring</code></li><li><code>/api/gsifi-aims/credit-underwriting/regulator</code></li><li><code>/api/gsifi-aims/roadmap</code></li><li><code>/api/gsifi-aims/roadmap/phases</code></li><li><code>/api/gsifi-aims/roadmap/phases/:id</code></li><li><code>/api/gsifi-aims/roadmap/kpis</code></li><li><code>/api/gsifi-aims/roadmap/risks</code></li><li><code>/api/gsifi-aims/operating-model</code></li><li><code>/api/gsifi-aims/operating-model/lod</code></li><li><code>/api/gsifi-aims/operating-model/raci</code></li><li><code>/api/gsifi-aims/operating-model/committees</code></li><li><code>/api/gsifi-aims/reporting</code></li><li><code>/api/gsifi-aims/reporting/audience</code></li><li><code>/api/gsifi-aims/reporting/template</code></li><li><code>/api/gsifi-aims/reporting/principles</code></li><li><code>/api/gsifi-aims/schemas</code></li><li><code>/api/gsifi-aims/schemas/:name</code></li><li><code>/api/gsifi-aims/code-examples</code></li><li><code>/api/gsifi-aims/code-examples/:name</code></li><li><code>/api/gsifi-aims/case-studies</code></li><li><code>/api/gsifi-aims/case-studies/:id</code></li><li><code>/api/gsifi-aims/modules</code></li><li><code>/api/gsifi-aims/modules/:id</code></li><li><code>/api/gsifi-aims/sections/:id</code></li><li><code>/api/gsifi-aims/m1</code></li><li><code>/api/gsifi-aims/m2</code></li><li><code>/api/gsifi-aims/m3</code></li><li><code>/api/gsifi-aims/m4</code></li><li><code>/api/gsifi-aims/m5</code></li><li><code>/api/gsifi-aims/m6</code></li><li><code>/api/gsifi-aims/m7</code></li><li><code>/api/gsifi-aims/m8</code></li><li><code>/api/gsifi-aims/m9</code></li><li><code>/api/gsifi-aims/m10</code></li><li><code>/api/gsifi-aims/m11</code></li><li><code>/api/gsifi-aims/m12</code></li></ul>
+  </section>
+</main>
+<footer>
+  © GSIFI-AIMS-BLUEPRINT-WP-037 v1.0.0 ·
+  2026-04-30 · CONFIDENTIAL — Board / Prudential Regulator / Group Risk / Internal Audit / Chief Legal &amp; Compliance Officer ·
+  Owner: Group CRO + Chief AI Officer (CAIO) — co-signed by CCO, GC, CISO, DPO, Head of Internal Audit
+</footer>
+</body>
+</html>
diff --git a/rag-agentic-dashboard/server.js b/rag-agentic-dashboard/server.js
index 86f82a3..b51897c 100644
--- a/rag-agentic-dashboard/server.js
+++ b/rag-agentic-dashboard/server.js
@@ -21739,6 +21739,236 @@ app.get('/api/wfap-gemini/case-studies/:id',      (req, res) => {
   res.json(cs);
 });
 
+// ══════════════════════════════════════════════════════════════════════════════
+//  GSIFI-AIMS-BLUEPRINT-WP-037 — Regulator-Grade AI Governance & ISO/IEC 42001
+//  AIMS Master Blueprint for G-SIFIs (2026–2030)
+// ══════════════════════════════════════════════════════════════════════════════
+const GSAIMS = require('./data/gsifi-aims-blueprint.json');
+
+const GSAIMS_MODULES = {
+  M1: GSAIMS.M1_aimsSections,
+  M2: GSAIMS.M2_aimsAnnexes,
+  M3: GSAIMS.M3_regulatoryOverlays,
+  M4: GSAIMS.M4_rsp,
+  M5: GSAIMS.M5_technicalEnforcement,
+  M6: GSAIMS.M6_adversarialSelfHealing,
+  M7: GSAIMS.M7_predictiveFormal,
+  M8: GSAIMS.M8_federationSupervisory,
+  M9: GSAIMS.M9_creditUnderwriting,
+  M10: GSAIMS.M10_roadmap,
+  M11: GSAIMS.M11_operatingModel,
+  M12: GSAIMS.M12_reportingDisclosure,
+};
+
+function gsaimsSection(modKey, sid) {
+  const mod = GSAIMS[modKey] || {};
+  return ((mod.sections) || []).find(s => (s.id || '').toUpperCase() === sid.toUpperCase()) || {};
+}
+
+app.get('/api/gsifi-aims',                  (_, res) => res.json(GSAIMS));
+app.get('/api/gsifi-aims/meta',             (_, res) => res.json(GSAIMS.meta || {}));
+app.get('/api/gsifi-aims/executive-summary',(_, res) => res.json(GSAIMS.executiveSummary || {}));
+app.get('/api/gsifi-aims/summary', (_, res) => {
+  const m = GSAIMS.meta || {};
+  const inv = m.deliverableInventory || {};
+  res.json({
+    docRef: m.docRef,
+    version: m.version,
+    title: m.title,
+    horizon: m.horizon,
+    classification: m.classification,
+    modules: Object.keys(GSAIMS_MODULES).length,
+    aimsSections: inv.aimsSections || 5,
+    annexes: inv.annexes || 4,
+    regulatoryOverlays: inv.regulatoryOverlays || 5,
+    rspVersions: inv.rspVersions || 7,
+    schemas: Object.keys(GSAIMS.schemas || {}).length,
+    codeExamples: Object.keys(GSAIMS.codeExamples || {}).length,
+    caseStudies: (GSAIMS.caseStudies || []).length,
+    phases: inv.phases || 5,
+    kpis: inv.kpis || 16,
+    controls: inv.controls || 280,
+    apiPrefix: '/api/gsifi-aims',
+    routes: ((GSAIMS.apiEndpoints || {}).routes || []).length,
+  });
+});
+
+app.get('/api/gsifi-aims/modules', (_, res) => {
+  res.json(Object.entries(GSAIMS_MODULES).map(([k, v]) => ({
+    key: k, id: (v && v.id) || k, title: (v && v.title) || '',
+    sections: ((v && v.sections) || []).length,
+  })));
+});
+app.get('/api/gsifi-aims/modules/:id', (req, res) => {
+  const id = req.params.id.toUpperCase();
+  const mod = GSAIMS_MODULES[id];
+  if (!mod) return res.status(404).json({ error: 'module not found', id: req.params.id });
+  res.json(mod);
+});
+
+// Module shortcuts m1..m12
+app.get('/api/gsifi-aims/m1',  (_, res) => res.json(GSAIMS.M1_aimsSections           || {}));
+app.get('/api/gsifi-aims/m2',  (_, res) => res.json(GSAIMS.M2_aimsAnnexes            || {}));
+app.get('/api/gsifi-aims/m3',  (_, res) => res.json(GSAIMS.M3_regulatoryOverlays     || {}));
+app.get('/api/gsifi-aims/m4',  (_, res) => res.json(GSAIMS.M4_rsp                    || {}));
+app.get('/api/gsifi-aims/m5',  (_, res) => res.json(GSAIMS.M5_technicalEnforcement   || {}));
+app.get('/api/gsifi-aims/m6',  (_, res) => res.json(GSAIMS.M6_adversarialSelfHealing || {}));
+app.get('/api/gsifi-aims/m7',  (_, res) => res.json(GSAIMS.M7_predictiveFormal       || {}));
+app.get('/api/gsifi-aims/m8',  (_, res) => res.json(GSAIMS.M8_federationSupervisory  || {}));
+app.get('/api/gsifi-aims/m9',  (_, res) => res.json(GSAIMS.M9_creditUnderwriting     || {}));
+app.get('/api/gsifi-aims/m10', (_, res) => res.json(GSAIMS.M10_roadmap               || {}));
+app.get('/api/gsifi-aims/m11', (_, res) => res.json(GSAIMS.M11_operatingModel        || {}));
+app.get('/api/gsifi-aims/m12', (_, res) => res.json(GSAIMS.M12_reportingDisclosure   || {}));
+
+// AIMS sections / annexes (M1, M2)
+app.get('/api/gsifi-aims/aims',                (_, res) => res.json(GSAIMS.M1_aimsSections || {}));
+app.get('/api/gsifi-aims/aims/sections',       (_, res) => res.json((GSAIMS.M1_aimsSections || {}).sections || []));
+app.get('/api/gsifi-aims/aims/sections/:id',   (req, res) => {
+  const id = req.params.id.toUpperCase();
+  const s = ((GSAIMS.M1_aimsSections || {}).sections || []).find(x => (x.id || '').toUpperCase() === id);
+  if (!s) return res.status(404).json({ error: 'AIMS section not found', id: req.params.id });
+  res.json(s);
+});
+app.get('/api/gsifi-aims/aims/annexes',        (_, res) => res.json((GSAIMS.M2_aimsAnnexes || {}).sections || []));
+app.get('/api/gsifi-aims/aims/annexes/:id',    (req, res) => {
+  const id = req.params.id.toUpperCase();
+  const s = ((GSAIMS.M2_aimsAnnexes || {}).sections || []).find(x => (x.id || '').toUpperCase() === id);
+  if (!s) return res.status(404).json({ error: 'AIMS annex not found', id: req.params.id });
+  res.json(s);
+});
+
+// Regulatory overlays (M3)
+app.get('/api/gsifi-aims/regulatory',           (_, res) => res.json(GSAIMS.M3_regulatoryOverlays || {}));
+app.get('/api/gsifi-aims/regulatory/overlays',  (_, res) => {
+  const sec = gsaimsSection('M3_regulatoryOverlays', 'M3-S1');
+  res.json(sec.overlays || []);
+});
+app.get('/api/gsifi-aims/regulatory/overlays/:id', (req, res) => {
+  const id = req.params.id.toUpperCase();
+  const sec = gsaimsSection('M3_regulatoryOverlays', 'M3-S1');
+  const o = (sec.overlays || []).find(x => (x.id || '').toUpperCase() === id);
+  if (!o) return res.status(404).json({ error: 'overlay not found', id: req.params.id });
+  res.json(o);
+});
+app.get('/api/gsifi-aims/regulatory/precedence',(_, res) => res.json(gsaimsSection('M3_regulatoryOverlays', 'M3-S2')));
+app.get('/api/gsifi-aims/regulatory/matrix',    (_, res) => res.json(gsaimsSection('M3_regulatoryOverlays', 'M3-S3')));
+
+// Regulator Submission Packs (M4)
+app.get('/api/gsifi-aims/rsp',                 (_, res) => res.json(GSAIMS.M4_rsp || {}));
+app.get('/api/gsifi-aims/rsp/versions',        (_, res) => {
+  const sec = gsaimsSection('M4_rsp', 'M4-S1');
+  res.json(sec.versions || []);
+});
+app.get('/api/gsifi-aims/rsp/versions/:id',    (req, res) => {
+  const id = req.params.id.toUpperCase();
+  const sec = gsaimsSection('M4_rsp', 'M4-S1');
+  const v = (sec.versions || []).find(x => (x.id || '').toUpperCase() === id);
+  if (!v) return res.status(404).json({ error: 'RSP version not found', id: req.params.id });
+  res.json(v);
+});
+app.get('/api/gsifi-aims/rsp/structure',       (_, res) => res.json(gsaimsSection('M4_rsp', 'M4-S2')));
+app.get('/api/gsifi-aims/rsp/api',             (_, res) => res.json(gsaimsSection('M4_rsp', 'M4-S3')));
+app.get('/api/gsifi-aims/rsp/pipeline',        (_, res) => res.json(gsaimsSection('M4_rsp', 'M4-S4')));
+
+// Technical enforcement (M5)
+app.get('/api/gsifi-aims/enforcement',           (_, res) => res.json(GSAIMS.M5_technicalEnforcement || {}));
+app.get('/api/gsifi-aims/enforcement/terraform', (_, res) => res.json(gsaimsSection('M5_technicalEnforcement', 'M5-S1')));
+app.get('/api/gsifi-aims/enforcement/opa',       (_, res) => res.json(gsaimsSection('M5_technicalEnforcement', 'M5-S2')));
+app.get('/api/gsifi-aims/enforcement/audit',     (_, res) => res.json(gsaimsSection('M5_technicalEnforcement', 'M5-S3')));
+
+// Adversarial / self-healing (M6)
+app.get('/api/gsifi-aims/adversarial',           (_, res) => res.json(GSAIMS.M6_adversarialSelfHealing || {}));
+app.get('/api/gsifi-aims/adversarial/loop',      (_, res) => res.json(gsaimsSection('M6_adversarialSelfHealing', 'M6-S1')));
+app.get('/api/gsifi-aims/adversarial/playbooks', (_, res) => res.json(gsaimsSection('M6_adversarialSelfHealing', 'M6-S2')));
+app.get('/api/gsifi-aims/adversarial/kpis',      (_, res) => res.json(gsaimsSection('M6_adversarialSelfHealing', 'M6-S3')));
+
+// Predictive / formal verification (M7)
+app.get('/api/gsifi-aims/predictive',             (_, res) => res.json(GSAIMS.M7_predictiveFormal || {}));
+app.get('/api/gsifi-aims/predictive/forecasters', (_, res) => res.json(gsaimsSection('M7_predictiveFormal', 'M7-S1')));
+app.get('/api/gsifi-aims/predictive/formal',      (_, res) => res.json(gsaimsSection('M7_predictiveFormal', 'M7-S2')));
+app.get('/api/gsifi-aims/predictive/causal',      (_, res) => res.json(gsaimsSection('M7_predictiveFormal', 'M7-S3')));
+
+// Federation / autonomous supervisory (M8)
+app.get('/api/gsifi-aims/federation',             (_, res) => res.json(GSAIMS.M8_federationSupervisory || {}));
+app.get('/api/gsifi-aims/federation/protocol',    (_, res) => res.json(gsaimsSection('M8_federationSupervisory', 'M8-S1')));
+app.get('/api/gsifi-aims/federation/tiers',       (_, res) => res.json(gsaimsSection('M8_federationSupervisory', 'M8-S2')));
+app.get('/api/gsifi-aims/federation/privacy',     (_, res) => res.json(gsaimsSection('M8_federationSupervisory', 'M8-S3')));
+app.get('/api/gsifi-aims/federation/joint-exam',  (_, res) => res.json(gsaimsSection('M8_federationSupervisory', 'M8-S4')));
+
+// Credit underwriting use case (M9)
+app.get('/api/gsifi-aims/credit-underwriting',                  (_, res) => res.json(GSAIMS.M9_creditUnderwriting || {}));
+app.get('/api/gsifi-aims/credit-underwriting/scope',            (_, res) => res.json(gsaimsSection('M9_creditUnderwriting', 'M9-S1')));
+app.get('/api/gsifi-aims/credit-underwriting/data',             (_, res) => res.json(gsaimsSection('M9_creditUnderwriting', 'M9-S2')));
+app.get('/api/gsifi-aims/credit-underwriting/dev-validation',   (_, res) => res.json(gsaimsSection('M9_creditUnderwriting', 'M9-S3')));
+app.get('/api/gsifi-aims/credit-underwriting/decisioning',      (_, res) => res.json(gsaimsSection('M9_creditUnderwriting', 'M9-S4')));
+app.get('/api/gsifi-aims/credit-underwriting/monitoring',       (_, res) => res.json(gsaimsSection('M9_creditUnderwriting', 'M9-S5')));
+app.get('/api/gsifi-aims/credit-underwriting/regulator',        (_, res) => res.json(gsaimsSection('M9_creditUnderwriting', 'M9-S6')));
+
+// Roadmap (M10)
+app.get('/api/gsifi-aims/roadmap',           (_, res) => res.json(GSAIMS.M10_roadmap || {}));
+app.get('/api/gsifi-aims/roadmap/phases',    (_, res) => {
+  const sec = gsaimsSection('M10_roadmap', 'M10-S1');
+  res.json(sec.phases || []);
+});
+app.get('/api/gsifi-aims/roadmap/phases/:id', (req, res) => {
+  const id = req.params.id.toUpperCase();
+  const sec = gsaimsSection('M10_roadmap', 'M10-S1');
+  const p = (sec.phases || []).find(x => (x.id || '').toUpperCase() === id);
+  if (!p) return res.status(404).json({ error: 'phase not found', id: req.params.id });
+  res.json(p);
+});
+app.get('/api/gsifi-aims/roadmap/kpis',  (_, res) => {
+  const sec = gsaimsSection('M10_roadmap', 'M10-S2');
+  res.json(sec.kpis || []);
+});
+app.get('/api/gsifi-aims/roadmap/risks', (_, res) => {
+  const sec = gsaimsSection('M10_roadmap', 'M10-S3');
+  res.json(sec.risks || []);
+});
+
+// Operating model (M11)
+app.get('/api/gsifi-aims/operating-model',             (_, res) => res.json(GSAIMS.M11_operatingModel || {}));
+app.get('/api/gsifi-aims/operating-model/lod',         (_, res) => res.json(gsaimsSection('M11_operatingModel', 'M11-S1')));
+app.get('/api/gsifi-aims/operating-model/raci',        (_, res) => res.json(gsaimsSection('M11_operatingModel', 'M11-S2')));
+app.get('/api/gsifi-aims/operating-model/committees',  (_, res) => res.json(gsaimsSection('M11_operatingModel', 'M11-S3')));
+
+// Reporting & disclosure (M12)
+app.get('/api/gsifi-aims/reporting',             (_, res) => res.json(GSAIMS.M12_reportingDisclosure || {}));
+app.get('/api/gsifi-aims/reporting/audience',    (_, res) => res.json(gsaimsSection('M12_reportingDisclosure', 'M12-S1')));
+app.get('/api/gsifi-aims/reporting/template',    (_, res) => res.json(gsaimsSection('M12_reportingDisclosure', 'M12-S2')));
+app.get('/api/gsifi-aims/reporting/principles',  (_, res) => res.json(gsaimsSection('M12_reportingDisclosure', 'M12-S3')));
+
+// Generic section lookup
+app.get('/api/gsifi-aims/sections/:id', (req, res) => {
+  const id = req.params.id.toUpperCase();
+  for (const mod of Object.values(GSAIMS_MODULES)) {
+    const s = ((mod && mod.sections) || []).find(x => (x.id || '').toUpperCase() === id);
+    if (s) return res.json(s);
+  }
+  return res.status(404).json({ error: 'section not found', id: req.params.id });
+});
+
+// Schemas / code examples / case studies
+app.get('/api/gsifi-aims/schemas',          (_, res) => res.json(GSAIMS.schemas || {}));
+app.get('/api/gsifi-aims/schemas/:name',    (req, res) => {
+  const sch = (GSAIMS.schemas || {})[req.params.name];
+  if (!sch) return res.status(404).json({ error: 'schema not found', name: req.params.name });
+  res.json(sch);
+});
+app.get('/api/gsifi-aims/code-examples',          (_, res) => res.json(GSAIMS.codeExamples || {}));
+app.get('/api/gsifi-aims/code-examples/:name',    (req, res) => {
+  const c = (GSAIMS.codeExamples || {})[req.params.name];
+  if (!c) return res.status(404).json({ error: 'code example not found', name: req.params.name });
+  res.json(c);
+});
+app.get('/api/gsifi-aims/case-studies',          (_, res) => res.json(GSAIMS.caseStudies || []));
+app.get('/api/gsifi-aims/case-studies/:id',      (req, res) => {
+  const u = req.params.id.toUpperCase();
+  const cs = (GSAIMS.caseStudies || []).find(c => (c.id || '').toUpperCase() === u);
+  if (!cs) return res.status(404).json({ error: 'case study not found', id: req.params.id });
+  res.json(cs);
+});
+
 // SECTION 10: START SERVER
 // ══════════════════════════════════════════════════════════════════════════════