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FRM Part II · FRM Exam Part II · Advances in Artificial Intelligence: Implications for Capital Markets Activities

A risk manager notes that AI models used for credit and market decisions may perform poorly in a regime unlike the data they were trained on. Which risk does this primarily represent, and what is a suitable mitigant?

This is model risk, specifically weak robustness outside the training data regime. Appropriate mitigants include stress testing models under novel scenarios, monitoring for performance drift and keeping meaningful human oversight, rather than relying on settlement, hedging or funding measures.

  1. AModel risk from limited out-of-sample robustness; mitigate with stress testing, ongoing monitoring and human oversightCorrect
  2. BSettlement risk; mitigate with delivery-versus-payment arrangements
  3. CBasis risk; mitigate by lengthening the maturity of hedges
  4. DFunding liquidity risk; mitigate by increasing the share of short-term wholesale funding

Explanation

Poor performance outside the training distribution is a model risk issue related to robustness and data drift. Scenario stress testing, monitoring for drift and human oversight are the appropriate controls; the other options address unrelated risks.

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