AI model risk governance
AI Model Risk Governance
AI and model-related use cases need governance that covers ownership, inventory, validation, performance monitoring, change control, and documentation.
Current model risk expectations
Current model risk language should reflect updated supervisory expectations, including SR 26-2 / OCC Bulletin 2026-13, while retaining SR 11-7 mapping where legacy documentation still uses it.
Evidence to maintain
Useful evidence includes model inventories, validation records, assumptions and limitations, monitoring results, change logs, and issue remediation status.
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