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 05, 2026

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Question 1

An insurance company is using a neural network for classifying claims as "Fraudulent" or "Non-Fraudulent." They decide to use ReLU (Rectified Linear Unit) as the activation function for the hidden layers. What is the primary purpose of using an activation function like ReLU in this neural network?

A : To scale the output between 0 and 1

B : To introduce non-linearity

C : To calculate weights in the hidden layers

D : To set bias terms to zero

Answer: B

Question 2

A justice system uses an AI model to predict failure-to-appear (FTA) rates in court. To ensure fairness without explicitly using protected group data, what could be a potential unintended outcome?

A : The model underestimates FTA for all demographics

B : The model’s accuracy decreases for high-risk groups

C : The model’s reliance on correlated variables increases potential bias in predictions

D : The model achieves demographic parity but lacks predictive accuracy

Answer: C

Question 3

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 4

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 5

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

Page: 1 / 66

Total 330 Questions | Updated On: Jan 05, 2026

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