Question 1

A risk management team is evaluating the QRM results of a newly developed credit risk model. The model output shows a low risk estimate, and team members are confident in their decision to proceed with increased exposure. However, they fail to consider that the model does not account for current market volatility. What critical factor did they overlook in interpreting the results?

Options :

A : Point estimates provide accurate assessments.

B : Risk model assumptions can be ignored.

C : Quantitative data is more reliable than qualitative.

D : Model limitations should be considered, especially unmodeled risks.

Answer: D

Question 2

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?

Options :

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 3

A generative AI provider in China is designing its service to align with Chinese regulations. What is a key obligation it must meet under the Generative AI Measures?

Options :

A : Ensure all content generated is free from any factual errors.

B : Prioritize content generation for government-endorsed topics only.

C : Prevent the generation of illegal and discriminatory content, respecting privacy rights.

D : Avoid transparency in algorithm usage to maintain competitive advantage.

Answer: C

Question 4

An admissions committee decides to incorporate a measure of resilience alongside grades in its AI-based selection criteria. Which challenge is the committee likely to face with this approach to individual fairnes

Options :

A : Defining resilience as a measurable trait

B : Avoiding direct discrimination

C : Ensuring grades remain the sole basis for admissions

D : Guaranteeing equal admissions for all applicants

Answer: A

Question 5

You are given the following feature vector and statistical parameters:

Feature Vector: [1, 3.6, 9, 10]

Mean: 5

Variance: 2.89

What is the standardized feature vector?

Options :

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

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