Free GARP RAI Exam Questions

Question 1

A game developer uses a multi-arm bandit model to recommend different in-game offers to players. The model tracks which offers players respond to and adjusts future recommendations accordingly. In MAB terms, what is the purpose of the "policy" in this context?

A : To measure player engagement levels

B : To maximize expected future rewards by recommending the best offers

C : To randomly assign offers to players without any learning

D : To ensure a fixed sequence of offers is presented to each player

Answer: B

Question 2

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

Question 3

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 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 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