- A
Data privacy of training data
Why wrong: Data privacy is important, but model bias is more directly tied to credit decision outcomes.
- B
Model drift due to changing economic conditions
Why wrong: Model drift affects accuracy but is not a primary regulatory concern.
- C
Model bias leading to unfair lending practices
Model bias can violate fair lending laws and result in regulatory fines and reputational damage.
- D
Adversarial attacks on the model
Why wrong: Adversarial attacks are a security risk but less likely to cause regulatory penalties directly.
Question 596 of 1,000
CRISC Information Technology and Security Practice Question
This CRISC practice question tests your understanding of information technology and security. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A financial institution is considering adopting a new AI/ML model for credit scoring. The model uses customer demographic data and transaction history. Which of the following risks is MOST likely to cause regulatory penalties if not addressed?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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 leading to unfair lending practices
Regulators require explainability for credit decisions to ensure fairness and compliance with regulations like ECOA and GDPR. Model bias can lead to discriminatory outcomes, resulting in significant penalties.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Data privacy of training data
Why it's wrong here
Data privacy is important, but model bias is more directly tied to credit decision outcomes.
- ✗
Model drift due to changing economic conditions
Why it's wrong here
Model drift affects accuracy but is not a primary regulatory concern.
- ✓
Model bias leading to unfair lending practices
Why this is correct
Model bias can violate fair lending laws and result in regulatory fines and reputational damage.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Adversarial attacks on the model
Why it's wrong here
Adversarial attacks are a security risk but less likely to cause regulatory penalties directly.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the CRISC exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which CRISC exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
- →
Information Technology and Security — study guide chapter
Learn the concepts, then practise the questions
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FAQ
Questions learners often ask
What does this CRISC question test?
Information Technology and Security — This question tests Information Technology and Security — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Model bias leading to unfair lending practices — Regulators require explainability for credit decisions to ensure fairness and compliance with regulations like ECOA and GDPR. Model bias can lead to discriminatory outcomes, resulting in significant penalties.
What should I do if I get this CRISC question wrong?
Identify which CRISC exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
This CRISC 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 CRISC exam.
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