Free GARP RAI Exam Questions

Become GARP Certified with updated RAI exam questions and correct answers

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Total 330 Questions | Updated On: Mar 20, 2026

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Question 1

During training, an RNN model used for forecasting exhibits extremely high gradients at certain steps, causing instability in learning. Which of the following best describes this problem?

A : Vanishing gradient

B : Exploding gradient

C : Overfitting

D : Gradient clipping

Answer: B

Question 2

Which term best describes a dataset that includes a mix of organized, structured financial data and unstructured text data from customer reviews?

A : Structured data

B : Unstructured data

C : Semi-structured data

D : Binary data

Answer: C

Question 3

While using Naïve Bayes for text classification, a bank wants to classify customer feedback as “Good” or “Bad.” How does the model handle the probability of classifying feedback with words it hasn’t encountered?

A : It assigns zero probability to the class if a new word is present.

B : It ignores the new word in classification.

C : It calculates probabilities based on prior data alone.

D : It smooths probabilities to avoid zero probabilities.

Answer: D

Question 4

A company wants to apply reinforcement learning to manage its warehouse inventory, learning when to restock based on demand fluctuations. What is a potential drawback of using reinforcement learning in this scenario?

A : It cannot adapt to new demand patterns over time.

B : It requires high amounts of labeled data for training.

C : It may initially perform poorly as it learns from trial-and-error.

D : It only works for supervised learning tasks.

Answer: C

Question 5

Which of the following scenarios represents a binary classification problem?

A : Predicting the probability of different stock prices

B : Forecasting next month’s sales in dollars

C : Determining if a transaction is fraudulent or legitimate

D : Grouping customers into three income tiers

Answer: C

Page: 1 / 66

Total 330 Questions | Updated On: Mar 20, 2026

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