AI Governance for Financial Services
Financial services firms operate under some of the most prescriptive AI regulations in any industry, with overlapping federal and state requirements governing automated decision-making. The primary driver is regulatory compliance across SEC, OCC, and CFPB frameworks that demand rigorous model risk management and fair lending protections. A governance program must address model validation, explainability for adverse actions, and continuous monitoring of AI systems used in lending, trading, and advisory functions.
Key Regulations
- SEC Guidance on AI in Investment Advisory
- OCC Guidance on Model Risk Management (SR 11-7)
- EU AI Act High-Risk Classification for Credit Scoring
- CFPB Fair Lending Requirements for Automated Decisions
- FFIEC Guidance on Third-Party Risk Management
Top AI Risks
- Discriminatory lending or credit decisions from biased AI models
- Model drift in trading algorithms causing undetected financial exposure
- Inadequate explainability for AI-driven customer adverse actions
- Unauthorized use of AI tools for market analysis without compliance review
Policy Requirements
- Model risk management framework aligned with SR 11-7 for all AI systems
- Fair lending bias testing protocols for AI-driven credit and underwriting decisions
- Explainability requirements for automated adverse action notices
- AI vendor due diligence process with SOC 2 and data residency verification
- Ongoing model performance monitoring with drift detection thresholds
- Board-level AI risk reporting cadence and escalation procedures
PolicyGuard provides financial services firms with SR 11-7 aligned model risk management workflows that track every AI system from validation through ongoing monitoring. The platform produces examination-ready documentation including bias testing reports, model performance logs, and vendor due diligence records that satisfy OCC and SEC audit requirements.
