Model risk management
The broader financial-sector discipline of identifying, measuring, monitoring, and controlling the risk that a model (AI-based or otherwise) behaves unexpectedly or is used incorrectly. The AIRG applies model risk management's established logic specifically to AI systems, adding the third-party delegation doctrine as an AI-specific sharpening of a much older discipline.
Defined in 2 GAGE programs, which carry 2 distinct definitions of it. The wording above is taught in Certified AI Governance Professional (CAIGP).
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
The broader financial-sector discipline of identifying, measuring, monitoring, and controlling the risk that a model (AI-based or otherwise) behaves unexpectedly or is used incorrectly. The AIRG applies model risk management's established logic specifically to AI systems, adding the third-party delegation doctrine as an AI-specific sharpening of a much older discipline.
The discipline of identifying, documenting, validating, and monitoring the risk that a quantitative model, including an AI model, produces incorrect or unreliable outputs that lead to poor business decisions.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- MAS runs the hardest AI regime in APAC, and it has never been a law · The World's Rulebooks, Certified AI Governance Professional (CAIGP)
- Financial Services and Insurance: NAIC, SR 11-7, CFPB, and the State Map · Sector Playbooks, The AI Lobbyist: Certified AI Policy Strategist
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.