AI-900 Practice Question: Describe Artificial Intelligence workloads and considerations
Which type of AI workload uses historical transaction data to identify potentially fraudulent transactions in real time?
⚠ Common exam trap
Many candidates confuse 'text generation' (Option C) with 'report generation' and mistakenly think summarizing transactions is the same as detecting fraud, when in fact fraud detection requires classification or anomaly detection, not natural language generation.
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
✓
Anomaly detection or classification to flag unusual transaction patterns
Anomaly detection and classification are AI techniques specifically designed to identify patterns that deviate from normal behavior. In fraud detection, historical transaction data is used to train a model that learns typical spending patterns, and then in real time, the model flags transactions that fall outside those learned patterns as potentially fraudulent.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Image captioning to describe transaction screenshots
Why it's wrong here
Image captioning produces natural-language descriptions of visual content, so it would describe what a transaction screenshot looks like rather than evaluate financial behavior. Fraud detection operates on structured transaction records—amount, merchant, time, frequency, device—not on images. Captioning a screenshot does not identify unusual patterns in that data, making it inappropriate for this task.
- ✓
Anomaly detection or classification to flag unusual transaction patterns
Why this is correct
Fraud detection is a classic supervised or unsupervised learning problem on transaction features. Classification models are trained on labeled historical transactions to predict whether a new transaction is fraudulent or legitimate, while anomaly detection identifies transactions that deviate significantly from a learned normal profile. These methods directly flag unusual patterns, such as sudden large transfers or rapid cross-border purchases, matching the definition of fraud detection.
- ✗
Text generation to create transaction summaries
Why it's wrong here
Text generation creates new human-readable content, such as a narrative summary of a transaction history, but it does not evaluate whether any transaction is suspicious. Fraud detection requires comparing real-time transactions against historical behavioral patterns to score risk, not producing descriptions. A generated summary could misrepresent or omit the very statistical deviations that signal fraud, so it is not the appropriate technique.
- ✗
Object detection to verify identity documents
Why it's wrong here
Object detection locates and classifies objects within an image by drawing bounding boxes, which is useful for extracting ID cards or passports from a photo. However, verifying an identity document is an optical or document-processing task, not a transaction-level fraud analysis. The question concerns detecting fraudulent financial activity from transaction records, where object detection has no role in modeling spending behavior.
Go deeper
Related to this question
Learn chapter
Regression and Classification
Key term
Model
In IT and AI, a model is a trained mathematical representation that learns patterns from data to make predictions or decisions.
Key term
Classification
Classification is a supervised machine learning technique used to predict a category or class label for new data based on patterns learned from labeled training data.
About these practice questions
This AI-900 question is part of Courseiva's 985-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-900 practice question is part of Courseiva's free Microsoft 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 AI-900 exam.