AI Readiness ยท Financial services
Where does your bank, insurer, asset manager, or fintech stand on AI readiness? Our financial-services bank aligns with SR 11-7 model risk management, NYDFS 500, SOX data governance, and ECOA-adjacent fairness practice.
What we reference
Sector-specific overlays on top of the generic 35-question bank โ so the findings speak the language your financial services reviewers already use.
Governance questions mirror independent validation, inventory, and performance monitoring expectations.
Vendor, incident response, and access-control questions reference this guidance where applicable.
Data-quality and lineage questions lean into SOX-grade controls, and PCI shows up in classification policy.
Fairness, transparency, and human oversight items reference the relevant AI Act articles.
Sample questions
Hereโs the kind of thing youโll answer in the financial services bank. Full assessment is 3ร longer โ still under 10 minutes.
Do you maintain a live model inventory with SR 11-7 classification and a designated model risk owner?
Do you perform independent model validation (second-line) before production rollout?
Do you run bias and fairness audits on models that influence credit, insurance, or treatment of customers?
These are samples. The real assessment adapts follow-ups based on your answers.
FAQ
The governance pillar explicitly references inventory, validation, and monitoring practices. It is not a substitute for SR 11-7 validation, but it highlights gaps against the spirit of the guidance.
Yes โ the data pillar includes an explicit bias and fairness question, and recommendations reference ECOA 1002 where relevant.
Financial services benchmarks cover all five pillars at 51-200, 201-1000, and 1001-5000 employee sizes, subject to the 30-sample minimum per segment.
Financial services bank
Sector overlays apply automatically. The result is a score, a peer benchmark and the three moves you can make this quarter โ tagged to the frameworks your reviewers already track.