AAIR AI Lifecycle Risk Management Practice Question
A financial institution uses an AI model to approve loans. After deployment, they notice the model is rejecting loan applications from a specific region at a rate 30% higher than historical human benchmarks. What is the most appropriate next step in the risk lifecycle?
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
✓
Conduct a bias investigation by comparing input distribution shifts between training data and current inference requests.
Investigation of bias requires a root cause analysis of input distributions and model weights compared to the baseline.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Ignore the shift as it may be a temporary market trend.
Why it's wrong here
A 30% deviation from historical human baselines is a significant indicator of potential algorithmic bias.
- ✓
Conduct a bias investigation by comparing input distribution shifts between training data and current inference requests.
Why this is correct
This identifies if the model is responding to a shift in input population or if the bias is inherent to the model logic.
- ✗
Immediately shut down the system.
Why it's wrong here
This is a business-disruptive action; further analysis is required first.
- ✗
Train a secondary model to override the primary one.
Why it's wrong here
Overriding models without understanding the root cause creates a 'black box' management nightmare.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official ISACA exam blueprint
This AAIR practice question is part of Courseiva's free ISACA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AAIR exam.