From Model risk, credit risk and quantitative analysis into AI governance
Can someone in model risk, credit risk and quantitative analysis move into AI governance?
SR 11-7 discipline, validation and independent challenge are the closest existing profession to AI assurance. Generative and agentic failure modes are what to add.
What you already carry
Credit before a single lesson. A work product counts as shown; experience you would describe counts as a claim. Neither is proof yet, and the graded path turns them into proof.
- Model risk management and independent challenge (shown by a work product)
Validation reports and model inventories are your record.
- AI evaluation and testing design (shown by a work product)
Test design and benchmark selection are the craft.
- How models work, at a governance depth (shown by a work product)
Quantitative fluency is demonstrated in your work.
- Post-deployment monitoring and drift detection (described, not yet shown)
Performance monitoring thresholds are familiar.
Roles this background reaches fastest
The closest 4 of the 50 roles on the map. Every role has its own page.
- Model Risk Manageryour background already covers 22%
Which systems count as models, what validation each tier needs, and which findings block deployment.
- AI Model Validatoryour background already covers 24%
Whether the evidence is sufficient, what the severity of each finding is, and under what conditions a model may be used.
- AI Evaluation Specialistyour background already covers 21%
What a score measures, what it misses, and whether the evidence supports release.
- AI Risk Manageryour background already covers 4%
Which risks need strong controls, which can be accepted, and when a use case should pause.
Where to start
Certified AI Governance Professional (CAIGP). The first module is free with a free account, and every topic is graded by explaining it back.
The percentages above count your background alone. Paste your CV on the readiness check and it counts too: work you built or led as shown, experience you describe as claimed. If you already have a GAGE account, every topic you have passed counts as proof.
Other backgrounds: Compliance and regulatory affairs, Internal audit and IT audit, Privacy and data protection, Cybersecurity and IT, Legal and paralegal work, Nonprofit program and grants oversight, Data analysis, stewardship and business intelligence, Human resources and people operations, Project and program management, Operations, claims, customer service and administration, Policy, legislative and government affairs staff, Recent graduate in law, policy, business or data, Teachers, trainers and instructional designers, Elder services, social work, banking front line and fraud teams, A law degree (JD, LLB or LLM), no AI work yet, A computer science or software engineering degree, A cybersecurity or information assurance degree, A public policy, political science or international relations degree, A business, MBA or technology management degree, A data science, statistics or analytics degree.