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FRM Part II · FRM Exam Part II · The Financial Stability Implications of Artificial Intelligence

A bank's model risk team is told that its generative AI credit-assessment tool is hard to explain and relies on opaque training data. Which approach is most consistent with the FSB's recommended focus on model risk and data quality?

The bank should strengthen model risk management and governance, including independent validation, explainability and data quality controls. Vendor testing, large datasets or cyber security checks alone do not address opacity, bias and data quality risks in AI models.

  1. AExempt the tool from validation because vendors tested it
  2. BStrengthen model risk management and governance, including validation, explainability and data quality controls, for AI modelsCorrect
  3. CAssume AI output is accurate if it was trained on large datasets
  4. DLimit review to cyber security controls

Explanation

The FSB identifies model risk, data quality and governance as vulnerabilities and encourages stronger frameworks for them. Vendor testing does not replace the bank's own validation, large data volume does not ensure quality, and cyber controls alone miss model risk.

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