AI Model Inventory and Model Risk Governance

A forty-hour Pro-level model-risk governance simulation run on a live model inventory transformation board, where you are Head of Model Risk Management at a UK bank with a US subsidiary whose register attests 412 of 412 models — until an uninventoried pricing spreadsheet misprices 41,200 loans and a discovery sweep finds 1,140; you measure the real gap, find and tier every model, give each a named owner, validate what matters first, monitor what runs, govern what you buy and the AI you adopt, build one system of record, price the programme at the margin and win a Board resolution everyone can be held to.

What you'll learn

• Measure model inventory completeness against discovery rather than attestation, define what counts as a model, and build discovery that keeps finding models across registries, code, end-user computing, vendors and generative AI.
• Tier models by materiality and complexity, assign accountable owners across the three lines, and prioritise independent validation, monitoring and decommissioning by risk.
• Govern vendor and generative-AI models through a shared intake gate and run the inventory as an audited system of record that generates its own key risk indicators.
• Price a model-risk transformation at the margin from named loss scenarios, set appetite and tolerances, prepare for supervisory and audit review, and win a Board resolution that can be tested.

Sign in to enrol — you can pay by bKash or Nagad, or apply a promo code.