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

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 2

Which type of risk might an organization face if an AI algorithm breaches individual privacy or yields biased results?

A : Existential risk

B : Operational risk

C : Reputational and regulatory risk

D : Environmental risk

Answer: C

Question 3

A financial institution is creating a model inventory. Which of the following should be included to ensure comprehensive governance?

A : Only the model’s purpose and validation report.

B : Model owner, but not developer information, for clarity.

C : A description of model assumptions but not its risk classification.

D : Model owner, purpose, methodology, assumptions, limitations, and risk tier.

Answer: D

Question 4

A financial institution is developing a credit risk model using a machine learning algorithm. The data science team decides to split their dataset into three parts: training, validation, and test sets. What is the primary purpose of the validation set in this setup?

A : To finalize the model by evaluating it on unseen data

B : To select the best performing model among multiple algorithms

C : To adjust model parameters to fit the training data

D : To test the model’s performance under different scenarios

Answer: B

Question 5

A tech firm is evaluating different models for an NLP project requiring high computational efficiency and parallel processing. Why might transformers be more suitable than RNNs for this task?

A : They use contextual embeddings

B : They are sequence-dependent

C : They allow for parallel processing

D : They rely on sequence ordering

Answer: C

Page: 1 / 66

Total 330 Questions | Updated On: Jan 05, 2026

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