Free GARP RAI Exam Questions

Question 1

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 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

A retail bank uses self-training to classify loan applicants as high or low risk, but it finds that updating the model after each new labeled data point is computationally intensive. Which approach can the bank use to reduce this burden?

A : Select multiple best-predicted instances in each round

B : Use an unsupervised learning model instead

C : Increase the complexity of the initial model

D : Use transductive learning instead

Answer: A

Question 4

A retail bank uses self-training to classify loan applicants as high or low risk, but it finds that updating the model after each new labeled data point is computationally intensive. Which approach can the bank use to reduce this burden?

A : Select multiple best-predicted instances in each round

B : Use an unsupervised learning model instead

C : Increase the complexity of the initial model

D : Use transductive learning instead

Answer: A

Question 5

During an NLS optimization, the analyst uses a gradient descent algorithm to update model parameters. If the improvement in the objective function falls below a certain threshold, the optimization process stops. What is the purpose of this threshold in NLS optimization?

A : To avoid overfitting by stopping after a set number of steps

B : To ensure convergence to the exact global minimum

C : To prevent unnecessary computations when further improvement is minimal

D : To improve model interpretability by limiting parameter updates

Answer: C