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
Where it shows up at work
A definition is where Model risk management starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Tracks executive orders, OMB guidance, agency rules and the state patchwork, and knows which state laws reach hiring, insurance and consumer decisions.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- AI Regulatory Counselneeds it at depth · 14 open postings this week
- AI Policy Analystneeds it at depth · 7 open postings this week
- Chief Compliance Officer, AI compliance editionneeds working knowledge
- VP of AI Governance and Ethicsneeds working knowledge
- Senior AI Compliance Analystneeds working knowledge
- AI Compliance Managerneeds working knowledge · 2 open postings this week
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: OMB M-25-21 and M-25-22; Colorado SB 24-205; NYC Local Law 144.
One interview question about it
A US company operates in several states. How do you track which state AI laws apply to which systems, and what changes when a new one passes?
Asked of candidates for us federal and state ai regulation. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- Policy, legislative and government affairs staff carries it as a claim to back up: You follow federal and state developments already.
- A public policy, political science or international relations degree carries it as a claim to back up: US federal and state process is familiar; the AI statutes are new.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.