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FRM Part I · FRM Exam Part I · Enterprise Risk Management and Future Trends

A bank's risk committee is reviewing its use of machine-learning models for credit scoring. Regulators have asked the bank to explain why individual applicants were declined. Which model-risk concern is most directly raised by this request?

The concern is model interpretability, or explainability. When complex machine-learning models decline applicants, the bank must be able to justify individual outcomes to regulators, and black-box algorithms make that hard. Liquidity, basis and settlement risks do not relate to explaining model decisions.

  1. AModel interpretability (explainability) of complex algorithmsCorrect
  2. BLiquidity risk arising from model outputs
  3. CBasis risk between model outputs and market prices
  4. DSettlement risk in model deployment

Explanation

Regulators asking for reasons behind individual decisions concerns explainability. Complex machine-learning models can behave as black boxes, making it hard to justify outputs. The other options are unrelated to explaining decisions.

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