Knowledge graph for fintech regulatory entities, obligations, disclosures, and AI-queryable compliance context.
- It turns fintech compliance into a structured entity problem instead of a document pile.
- It connects regulators, rules, products, obligations, controls, and disclosures in one traversable model.
- It exports JSON-LD so downstream AI systems can consume machine-readable compliance context.
- It complements
payment-event-ledger-eos,pulumi-pci-dss-baseline, andotel-fraud-signal-traceras part of a stronger fintech cluster.
- seeds a local graph of regulators, rules, firms, products, obligations, controls, and disclosures
- exposes graph summaries and entity filters through FastAPI routes
- resolves explainable relationship paths between high-risk products and control evidence
- exports the graph as JSON-LD for AI-queryable compliance context
- presents a polished HTML proof surface for overview, graph board, and evidence export
cd fintech-regulatory-knowledge-graph
py -3.11 -m pip install -r requirements.txt
py -3.11 -m app.mainOpen:
http://127.0.0.1:4591/http://127.0.0.1:4591/graphhttp://127.0.0.1:4591/evidencehttp://127.0.0.1:4591/docs
If the port is busy:
$env:PORT = "4595"
py -3.11 -m app.mainpy -3.11 -m pip install -r requirements.txt
py -3.11 -m pytest tests
py -3.11 scripts\run_demo.pyGET /api/summaryGET /api/entities?node_type=regulatorGET /api/path?start=sec&end=risk-disclosure-packGET /api/export/jsonldGET /api/sample



