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

A trading firm uses a deep neural network to generate short-term alpha signals. Risk management cannot explain why the model takes large positions in particular securities. Which control is most appropriate to address this specific concern?

Use explainability methods together with independent position and loss limits and human oversight. This addresses model opacity by constraining outcomes even when internal logic is hard to interpret, whereas more complexity or removing limits worsens risk.

  1. AApply explainability techniques and set independent position and loss limits with human oversightCorrect
  2. BIncrease the model's complexity to improve accuracy
  3. CRemove all limits since the model is optimized
  4. DRely solely on the vendor's performance claims

Explanation

Opacity is addressed by explainability tools (such as feature attribution) and by independent hard limits and human oversight that do not depend on understanding the model internals. More complexity worsens opacity, and removing limits raises risk.

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