AI is already sitting in credit, fraud, AML and reporting decisions. Governance has not caught up yet. These three questions show whether you have oversight or just exposure.
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THEINVENTORY2 / 5
01
Do we know every model
we run?
You cannot govern what you cannot see. Spreadsheets, vendor tools and the quiet AI features buried inside software you already pay for are all making calls. Start with a live model inventory: who owns it, what it does, what data it touches, how much risk it carries.
Model inventoryRisk tieringOwnership
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THEACCOUNTABILITY3 / 5
02
Who answers when
it gets it wrong?
A model cannot be held accountable. A person can. Put a named human behind every material model, and give them the authority to challenge it, override it and switch it off. Telling a regulator that the algorithm decided has never worked as a defence.
Named ownerOverride rightsAudit trail
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THECONTROL4 / 5
03
Can we explain it
and stop it?
Once a model is live it needs the same controls as any other risk. Watch it for drift, set thresholds that force a review, and test the kill switch before the day you need it. If you cannot explain a decision or pause the system, what you have is hope, not governance.
Drift monitoringExplainabilityKill switch
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GLOBAL RISKCLINIC5 / 5
Make AI
governable.
We help boards put AI governance in place that actually holds: a model inventory, clear accountability and live controls, across the full lifecycle.
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