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AI Concepts and FoundationsmediumMultiple ChoiceObjective-mapped

AI0-001 AI Concepts and Foundations Practice Question

An AI model for detecting fraudulent transactions has high precision but low recall. Which business impact is most likely?

⚠ Common exam trap

CompTIA often tests the distinction between precision and recall by presenting a scenario where candidates confuse high precision with high recall, leading them to incorrectly select option D (many legitimate transactions flagged) instead of recognizing that low recall causes undetected fraud.

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

Many fraudulent transactions go undetected

High precision means that when the model flags a transaction as fraudulent, it is very likely correct. However, low recall indicates that the model misses a significant proportion of actual fraudulent transactions. Therefore, the most likely business impact is that many fraudulent transactions go undetected, leading to financial losses.

Answer analysis

Option-by-option breakdown

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

  • The model has no impact on fraud detection

    Why it's wrong here

    It does detect some fraud, but misses many.

  • The model detects all fraudulent transactions

    Why it's wrong here

    Low recall means many are missed.

  • Many fraudulent transactions go undetected

    Why this is correct

    Low recall indicates a high number of false negatives.

  • Many legitimate transactions are flagged as fraud

    Why it's wrong here

    That would be low precision, not low recall.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.