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

A risk team uses a complex machine learning model to flag potential market manipulation. A regulator asks the firm to explain why a specific client's orders were flagged, but the model is a black box. Which response best aligns with sound practice for managing this risk?

The firm should use explainability techniques, documented model validation and human oversight so it can justify each alert. High accuracy alone does not satisfy supervisors, and sampling or disabling logs would weaken governance rather than address the opacity of the black-box model.

  1. ARely on the model's high backtested accuracy and decline to provide an explanation
  2. BApply explainability techniques and documented validation, retain human oversight, and be able to justify individual alertsCorrect
  3. CReplace the model with a random sample of trades to avoid explainability issues
  4. DDisable the model's logging to limit disclosure of proprietary logic

Explanation

Supervisors expect firms to understand and justify model outputs. Explainability tools, validation documentation and human oversight address opacity. Accuracy alone does not meet the need to justify individual decisions, and removing logs worsens governance.

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