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

A bank compares a transparent logistic regression with a deep neural network for a trade surveillance alert system. The neural network has higher predictive accuracy but its decisions are hard to explain to regulators. From a risk management perspective, which statement best describes the main issue created by the neural network?

The key issue is that limited explainability increases model risk and makes validation, governance and accountability harder. Regulators and risk managers must be able to understand and challenge model outputs, so higher accuracy does not remove the need for transparency and independent validation.

  1. AHigher accuracy always removes the need for model validation
  2. BLimited explainability raises model risk and complicates validation, governance and accountabilityCorrect
  3. CNeural networks cannot be applied to structured financial data
  4. DLogistic regression cannot produce probabilities, so it is unsuitable

Explanation

Opaque models make it harder to validate, challenge and justify outputs, increasing model risk and governance burden. Accuracy does not replace validation. Neural networks can be used on structured data, and logistic regression does output probabilities.

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