How do we meet SR 11-7 model risk management requirements for AI?

SR 11-7 requires independent model validation, ongoing monitoring, and documented model governance. Build a model registry capturing: intended use, assumptions, validation results, and performance benchmarks. Conduct independent validation before production deployment.

Can AI make automated lending decisions without human review?

Yes, with proper ECOA compliance. Automated decisions must include adverse action notices with specific reason codes. All decisions must be explainable, and the model must be validated for fair lending compliance across protected classes.

💰Regulatory Compliance

Finance Compliance

AI-powered fraud detection, algorithmic trading, credit risk scoring, and regulatory compliance automation for banks, fintechs, and financial services companies.

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Regulatory Landscape

Financial Services Compliance Architecture for AI Systems

Financial AI systems operate in one of the most regulated environments globally. SOX, PCI-DSS, GDPR, and Basel III each impose distinct requirements on AI architecture.

Sarbanes-Oxley (SOX)

High

Requires documented internal controls over financial reporting. AI systems affecting financial data must have complete audit trails and change management controls.

PCI-DSS v4.0

High

Payment Card Industry standard requiring encryption, access controls, and network security for any system handling cardholder data.

GDPR / CCPA

High

Data privacy regulations requiring explicit consent, right to explanation for automated decisions, data minimization, and right to erasure.

Basel III / IV

High

International banking regulations governing capital requirements, model risk management, and stress testing for AI-driven credit and risk models.

FINRA Rules

Medium

FINRA supervision rules require review and approval of AI-generated communications, audit trails for trading algorithms, and supervisory controls.

Compliance Challenges

Explainability requirements for AI credit decisions under ECOA

Model risk management (SR 11-7) validation for all AI models in production

Cross-border data transfer restrictions affecting AI training datasets

Real-time compliance monitoring for trading algorithms

Maintaining algorithmic accountability for automated lending decisions

Recommended Compliance Architecture

Model Risk Management Layer

Independent model validation, performance monitoring, and documentation meeting SR 11-7 requirements

Financial Data Vault

Encrypted financial data storage with field-level access controls and complete data lineage tracking

Compliance Audit Engine

Automated compliance checks against regulatory rules, with real-time alerting on violations

Explainability Framework

SHAP/LIME model explanations generated for every AI credit decision to meet ECOA adverse action requirements

Best Practices

Conduct quarterly model performance reviews against SR 11-7 standards

Maintain a model inventory with risk ratings for all production AI models

Implement automated ECOA adverse action reason code generation

Run annual penetration tests on all customer-facing financial AI systems

Establish a Model Risk Committee with CISO, CRO, and CDO representation

Frequently Asked Questions

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