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: Jan 13, 2026

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Question 1

You are given the following feature vector and statistical parameters:Feature Vector: [1, 3.6, 9, 10]Mean: 5Variance: 2.89What is the standardized feature vector?

A : [−2.35,−0.82, 2.35, 2.94]

B : [−2.34,−0.81, 1.81, 1.97]

C : [−1.81,−0.81, 2.34, 2.76]

D : [−2.34,−0.81, 2.34, 3.76]

Answer: A

Question 2

A financial institution is implementing an AI model that uses proxies for loan approval decisions. Which of the following is a potential risk associated with using proxies?

A : Proxies might result in simplified metrics that don’t align with the actual objective.

B : Proxies require extensive computational resources.

C : Proxies ensure a direct alignment with the model’s intended objective.

D : Proxies make the model fully explainable to external auditors.

Answer: A

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 financial services firm is using a neural network with multiple hidden layers to predict the likelihood of loan default (binary classification). They find that the model isn’t learning well with the logistic activation function in the hidden layers. Which activation function should they consider switching to improve learning?

A : Softmax

B : ReLU

C : Hyperbolic tangent

D : Sigmoid

Answer: B

Question 5

In cost complexity pruning, a bank uses a parameter, α, to balance the residual sum of squares (RSS) and the number of terminal nodes. What is the primary role of this parameter?

A : Maximize the training accuracy

B : Minimize the test set error

C : Control the trade-off between tree size and fit

D : Increase the complexity of the tree

Answer: C

Page: 1 / 66

Total 330 Questions | Updated On: Jan 13, 2026

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