AI governance for banks — what regulators actually want

Bank regulators want five things from an AI system: that policy was bound before the decision (not patched in afterwards), that every decision is explainable on demand, that model drift is monitored continuously, that the audit trail is tamper-evident and indemnified, and that human escalation paths cannot be silently bypassed by the machine.

In more depth

These are the five principles in 'Governing at the Speed of Thought' (SSRN preprint 6562738). They translate to concrete controls: a policy-as-code layer evaluated pre-inference; a per-call rationale store; a drift dashboard with named owners; signed, append-only decision logs; and an escalation route the model cannot suppress.

How JAQL approaches this

JAQL's AI Observability service implements these five controls for banking clients. See /frameworks/governing-at-the-speed-of-thought/ and the SSRN preprint.

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Published by Jumpstart AI and Quantum Labs. Co-founders: Dr. Nupur Mukherjee (Chief Science Officer) and Kishan Sathyan (Chief GTM Officer). Research cited as SSRN preprints; JAQL technology is quantum-inspired and runs on classical infrastructure.