A post-incident investigation finds that an AI-powered anti-money laundering system inadvertently allowed suspicious transactions because certain risk signals were disabled to reduce false…

The correct answer is B. Insufficient model validation and change control processes. The root cause is that a configuration change - disabling risk signals - was made without proper validation of the downstream impact. A mature change control process would require impact analysis, testing in a staging environment, and approval before any modification to a…

AI Security Strategy and Governance

Question

A post-incident investigation finds that an AI-powered anti-money laundering system inadvertently allowed suspicious transactions because certain risk signals were disabled to reduce false positives. Which of the following governance failures does this BEST demonstrate?

Options

ALack of sufficient computing resources for the AI system
BInsufficient model validation and change control processes
CExcessive reliance on external consultants for model design
DAbsence of metrics and dashboard for analysts

How the community answered

(47 responses)

A
6% (3)
B
77% (36)
C
15% (7)
D
2% (1)

Explanation

The root cause is that a configuration change - disabling risk signals - was made without proper validation of the downstream impact. A mature change control process would require impact analysis, testing in a staging environment, and approval before any modification to a production AI model. Model validation would have confirmed that removing those signals degraded detection capability. This is a textbook model validation and change control failure. Lack of computing resources (A), over-reliance on consultants (C), and absence of dashboards (D) are unrelated to the specific failure described.

Topics

#AI Governance#Model Validation#Change Control#AI Risk Management

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