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AI agent for chief digital officers

AI Model Risk Register Agent

A current register of live models with owners, reviews and risk status

AI Model Risk Register Agent: what goes in, what the agent does and what you get

What it does

Nobody knows which models are live, who owns them and when they were last reviewed. This agent reads the model inventory and monitoring data and checks each model for an owner, review date, performance and changes in its data. It flags overdue reviews and models whose accuracy or data has drifted. It requests evidence from the owners, such as a review note or test results, and checks again when it arrives. The risk committee approves any pause or retirement. Edge case: a model has no owner because the team was reorganized, so the agent flags it as unowned.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueApprovedNoNo 1 STARTS WHEN Monthly model review 2 USES A TOOL Read the model inventory and monitoring data 3 DOES Check each model for owner, review date and use 4 DOES Check performance and data drift against limits 5 CHECKS THE RESULT Does each model meet owner, review and performancerules? If not: flag the model and request evidence from theowner. Back to step 3. 6 USES A TOOL Send evidence requests to owners 7 DOES Review the evidence when it arrives 8 CHECKS THE RESULT Does the evidence close each flag? If not: mark the flag open and escalate after thedeadline. Back to step 3. 9 YOU APPROVE Risk committee approves any pause or retirement 10 RESULT Updated register and risk report
Read the steps as a list
  1. Monthly model review
  2. Read the model inventory and monitoring data
  3. Check each model for owner, review date and use
  4. Check performance and data drift against limits
  5. Does each model meet owner, review and performance rules?If not: flag the model and request evidence from the owner. Back to step 3.
  6. Send evidence requests to owners
  7. Review the evidence when it arrives
  8. Does the evidence close each flag?If not: mark the flag open and escalate after the deadline. Back to step 3.
  9. Risk committee approves any pause or retirementThe agent waits here for your OK.
  10. Updated register and risk report

How it decides

A model is flagged when it has no owner, its review is overdue, performance dropped below its limit or its input data changed a lot.

  • Flag a model with no owner
  • Flag a review overdue by 30 days or more
  • Flag performance below the stated limit
  • Escalate open flags after 30 days

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Review frequency per model (default: 12 months)
  • Performance limits
  • Drift limits
  • Escalation time

What keeps you in control

It always asks you first

  • Risk committee approves any pause or retirement

Hard limits

  • Never pauses a model itself
  • Never changes model settings

It stops when

  • Done: all flags are closed or decided
  • Stop: the model inventory is incomplete

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensThe review of 38 models flagged 5. One credit scoring model had no owner after a reorganization and a review 4 months overdue. Another showed drift in income data. The agent requested evidence. The owner for the second supplied a retest. The first stayed open. The committee approved pausing new use of the unowned model.

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