Jev, LLMs and the gap between confidence and authorization.
Decision models return bounded answers that software can act on directly. That makes agentic AI easier to govern, and raises a harder question: calibrated against what?
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Practitioner notes on Model Risk and AI governance.
Analysis and point-of-view writing on where AI governance and model risk practice is heading — drawn from active client work, not secondhand commentary.
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AI governance is a control infrastructure problem in a policy costume.
The challenge is no longer defining how AI should be governed. It is building the operational capacity to govern AI at the speed and scale at which it is being deployed.
Supervision just moved the goalposts. Model and AI risk fell outside them.
The OCC and FDIC have redrawn bank supervision around material financial harm. Read with SR 26-2, four separate routes to a supervisory finding on AI now miss — and the gap lands on the board. Five shifts, and a tailored pathway for community, regional and large banks and for fintechs.
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