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

A broker-dealer replaces its keyword-based trade communications surveillance with a natural language processing model that flags conversations by context and sentiment. Which benefit is most directly expected from this change relative to the keyword approach?

The main expected benefit is better detection of misconduct hidden in coded, paraphrased or new language, which fixed keyword lists miss. NLP reads context, but it still needs human review, produces some false positives, and carries model risk even when supplied by a vendor.

  1. AElimination of the need for human review of alerts
  2. BBetter detection of misconduct expressed in coded or novel language that fixed keyword lists missCorrect
  3. CGuaranteed reduction of false positives to zero
  4. DRemoval of model risk because the system is vendor supplied

Explanation

Context-aware NLP can pick up paraphrased or coded language that static keyword lists cannot, improving detection coverage. It does not remove human review, cannot guarantee zero false positives, and vendor models still carry model risk that the firm must validate.

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