AI Board Pack Builder

AI/ML Model Inventory and Risk Classification

Establishes visibility into where AI is in use and how each use case is classified.

Model Validation and Ongoing Monitoring

Confirms validation discipline and monitoring cadence consistent with model risk guidance.

Bias, Fairness, and Explainability

Addresses fair lending, UDAAP, and customer-impact considerations of AI decisions.

Generative AI Use Cases and Risk

Covers permitted use, data leakage, and policy enforcement for generative tools.

Third-Party AI and Vendor Model Risk

Extends model risk discipline into vendor and SaaS-embedded AI.

Regulatory Expectations (SR 11-7, OCC 2011-12)

Anchors the discussion in interagency model risk management guidance.

Board Reporting on AI/ML Performance

Defines the cadence and content of AI-related reporting to the board.

AI-Related Incident Response

Tests preparedness for AI-driven errors, outages, or harmful outputs.

Customer-Facing AI Applications

Examines AI in customer journeys including chatbots and decisioning.

AI Ethics and Governance Policy

Confirms the existence and currency of a board-approved governance policy.