A financial institution is deploying a credit-scoring model. The model was trained on historical data and validated on a holdout set. After deployment, the bank's risk team wants to ensure the model continues to perform well as economic conditions change. Which action best addresses the ongoing risk of model drift?

Increase the frequency of manual audits without automated monitoring.

Freeze the model parameters to prevent any changes that could introduce new risks.

Rely solely on the initial validation results to confirm long-term reliability.

Implement a monitoring process that tracks performance metrics and triggers retraining when drift is detected.

A global tech company is deploying an AI model that processes personal data of users in the EU, US, and Asia. The model is used for content recommendation. The company must comply with GDPR, CCPA, and other local laws. Which approach is most appropriate?

Use a single privacy policy for all regions to simplify compliance.

Comply only with GDPR since it is the strictest regulation.

Avoid processing personal data altogether to sidestep regulations.

Implement a privacy-by-design approach with data minimization and user consent mechanisms.

Which stage of the AI model lifecycle involves defining the problem, identifying data sources, and establishing success criteria before any model training occurs?

Problem definition and requirements gathering

ISACAAdvanced in AI Audit

Domain 1Objective 1

AI Models, Considerations, and Requirements AAIA Practice Questions (Page 6)

Part of the AI Governance and Risk domain, which accounts for 33% of the AAIA exam.

38questions here

8free pages

10concepts

33%of the exam

Questions 26–30

26application · medium
A financial institution is deploying a credit-scoring model. The model was trained on historical data and validated on a holdout set. After deployment, the bank's risk team wants to ensure the model continues to perform well as economic conditions change. Which action best addresses the ongoing risk of model drift?
Select an answer first
27expert · hard
A global tech company is deploying an AI model that processes personal data of users in the EU, US, and Asia. The model is used for content recommendation. The company must comply with GDPR, CCPA, and other local laws. Which approach is most appropriate?
Select an answer first
28foundation · easy
Which performance metric is most appropriate for a binary classification model when the cost of false negatives is much higher than the cost of false positives?
Select an answer first
29foundation · easy
Which stage of the AI model lifecycle involves defining the problem, identifying data sources, and establishing success criteria before any model training occurs?
Select an answer first
30foundation · easy
Which regulatory framework includes requirements for high-risk AI systems, including risk management and transparency obligations?
Select an answer first

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AI Models, Considerations, and Requirements AAIA Practice Questions (Page 6)

Questions 26–30

A global tech company is deploying an AI model that processes personal data of users in the EU, US, and Asia. The model is used for content recommendation. The company must comply with GDPR, CCPA, and other local laws. Which approach is most appropriate?

Which performance metric is most appropriate for a binary classification model when the cost of false negatives is much higher than the cost of false positives?

Which stage of the AI model lifecycle involves defining the problem, identifying data sources, and establishing success criteria before any model training occurs?

Which regulatory framework includes requirements for high-risk AI systems, including risk management and transparency obligations?

Keep studying — AI Governance and Risk