Financial Services — AIDF Blueprint
Executive Summary
Build provably compliant AI across credit, trading, fraud, and operations. AIDF encodes governance and ethics as controls‑as‑code with auditable evidence, mapping directly to SR 11‑7, SOX, Basel III, and privacy regulations.
Industry Context
- Regulatory pressure: SR 11‑7 model risk, fair lending, CCAR, Basel III
- Exposure: bias, data leakage, model drift, opaque decisioning
- Required posture: measurable controls, traceability, repeatable evidence
Reference Architecture (AIDF)
- Governance: approvals, risk tolerance, audit sink (JSONL/stdout)
- Ethics: bias methods, fairness metrics, explainability, audit cadence
- Memory: session, vector, RAG/CRAG, retention, PII handling
- Orchestrator: workflows, errors, resource controls, timers/metrics
- Monitoring: backend (Prometheus/Datadog), SLOs, alerts, anomalies
Controls Mapping (excerpt)
- SOX 302/404 → policy enforcement + approvals evidence (approvals.jsonl)
- Fair Lending → statistical parity/EO metrics + model cards
- Basel capital models → validation reports + stress harness outputs
- GLBA/GDPR → data minimization + retention proofs
Deliverables
- Control matrix (CSV/JSON) and evidence templates
- Canonical AIDF config per domain (governance/ethics/…)
- Audit/runbooks and CI checks (property tests, bias dashboards)
90‑Day Plan
- Diagnostic and control scoping; define KPIs and evidence
- Reference config + pilot (one decisioning flow)
- Bias/traceability dashboards; handoff with audit pack
KPIs
- Approval SLA, fairness deltas, drift score, time‑to‑evidence, audit defect rate
Next Steps
- Run the AIDF Diagnostic (select “Financial Services”)
- Receive a canonical config and schedule Architecture Review