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CRISC Information Technology and Security Practice Question

An organization is implementing an AI/ML model for credit approval decisions subject to regulatory oversight. Which TWO of the following are the most significant risk considerations?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Model bias causing discriminatory outcomes

Regulated decisions require explainability, and model bias can lead to unfair or illegal outcomes. Both are critical risks.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
Model bias causing discriminatory outcomes
Why this is correct
Bias can lead to legal and reputational damage.
✓
Model explainability for regulatory compliance
Why this is correct
Regulators may require clear explanations for credit decisions.
✗
Data privacy in AI training
Why it's wrong here
Important but secondary to bias and explainability in regulated decisions.
✗
High computational cost of model retraining
Why it's wrong here
Cost is an operational concern, not a risk for regulatory compliance.
✗
Adversarial attacks on the training data
Why it's wrong here
While a risk, it is less immediate than bias and explainability for credit approval.

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CRISC Information Technology and Security Practice Question

Why each option matters

Option-by-option breakdown

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