AI Risk Assessment Matrix - Financial Services Edition

Model risk assessment framework covering SR 11-7 compliance, fair lending risk (ECOA/FCRA), algorithmic trading risks, and third-party AI vendor assessment. Includes model tiering methodology and financial AI risk register templates.

Finance

Get This Resource Free

Create Free Account

Key Insights

Financial services AI carries unique risks that can result in regulatory enforcement, consumer harm, financial losses, and reputational damage. SR 11-7 requires model risk management for all models including AI. Fair lending laws prohibit discrimination—including by AI. Securities regulations govern algorithmic trading. Proper risk assessment isn't optional—it's a regulatory expectation.

This framework provides comprehensive risk assessment methodologies aligned with SR 11-7 Model Risk Management guidance, fair lending requirements, and securities regulations. It covers the specific risk categories that matter in financial services.

Overview

Financial AI risk assessment has regulatory requirements. SR 11-7 expects model risk management for AI. Fair lending examination will ask how you tested for discrimination. Your risk framework must address what regulators expect—generic risk assessment doesn't.

This framework provides financial services-specific risk assessment. It aligns with SR 11-7, addresses fair lending, covers trading AI, and provides the documentation regulators expect to see.

What's Inside

Financial Services-Specific Risk Categories

Model risk (SR 11-7)
Fair lending and discrimination risk
Market manipulation and trading risk
Consumer protection (UDAAP) risk
Cybersecurity and fraud risk
Third-party/vendor risk
Operational and compliance risk

1. Model Risk Assessment Framework
Aligned with SR 11-7 expectations:

Conceptual risk: Model design, assumptions, limitations
Implementation risk: Coding, integration, controls
Data risk: Quality, bias, representativeness, drift
Performance risk: Accuracy, stability, degradation
Risk scoring by model tier (Tier 1/2/3)

2. Fair Lending Risk Assessment

Disparate impact testing methodology
Proxy discrimination analysis
Protected class performance evaluation
Adverse action documentation requirements
Fair lending testing frequency and scope

3. Algorithmic Trading Risk Assessment

Market manipulation risk
Flash crash and stability risk
Best execution compliance
Spoofing and layering detection
Kill switch and circuit breaker requirements

4. Third-Party AI Risk Assessment

Vendor due diligence requirements
Model transparency expectations
Contractual requirements
Ongoing monitoring requirements
Concentration risk evaluation

5. Risk Scoring Methodology

Likelihood × Impact scoring
Financial services-specific impact factors (regulatory, consumer, financial)
Risk tier classification
Aggregation methodology

6. Risk Mitigation Strategies

Controls mapped to risk types
Implementation guidance
Effectiveness measurement

7. Risk Register Template

Financial services-adapted fields
Regulatory mapping
Audit trail requirements

8. Monitoring & Reassessment

Ongoing monitoring requirements
Reassessment triggers
Performance drift detection
Quarterly review process

Who This Is For

Chief Risk Officers managing AI in risk frameworks
Model Risk Management implementing AI risk assessment
Fair Lending Officers ensuring compliance
Compliance Officers preparing for examination
AI/ML Teams understanding risk requirements

Why This Resource

Financial services risk assessment must align with regulatory expectations. This framework addresses SR 11-7 model risk categories, fair lending testing requirements, and securities trading concerns—not generic risk factors you have to adapt. Examiners will recognize the framework alignment.

Fair lending risk assessment is detailed enough to satisfy examination expectations.

FAQ

Q: How does this align with SR 11-7?

A: The model risk assessment framework uses SR 11-7 risk categories (conceptual, implementation, data, performance) and tiering approach. It extends SR 11-7 to AI-specific considerations while maintaining regulatory alignment.

Q: What about fair lending testing for AI?

A: The fair lending risk assessment provides disparate impact testing methodology, proxy discrimination analysis, and documentation requirements. It covers what fair lending examination expects for AI credit decisions.

Q: Do we need separate risk assessment for trading AI?

A: Yes—algorithmic trading has distinct regulatory requirements and risk factors. The trading risk assessment section addresses market manipulation, stability, and securities compliance concerns that don't apply to other AI.