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 08, 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

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

Question 3

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

Question 4

A critical infrastructure provider in the U.S. wants to ensure responsible AI deployment to enhance service reliability. How should the provider proceed under guidance from the AI Safety and Security Board (AISSB)?

A : Only focus on AI deployment in non-critical areas to minimize risk.

B : Deploy AI solutions that solely increase service efficiency without security considerations.

C : Limit AI usage to what is already industry-standard to avoid compliance issues.

D : Implement recommendations from the AISSB to address AI-related disruptions to critical services, protecting national security and public health.

Answer: D

Question 5

A bank is developing its model risk governance framework to address ML/AI models. What foundational approach should the bank take?

A : Create an entirely new framework specific to AI/ML.

B : Build upon its existing model risk framework while adapting to new challenges from AI/ML.

C : Exclude traditional models from the risk framework.

D : Focus solely on AI/ML ethical aspects without considering statistical issues.

Answer: B

Page: 1 / 66

Total 330 Questions | Updated On: Mar 08, 2026

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