Preview Questions Risk Assessment Analyst | Role Specific Skill

Question 1: In a financial institution, what is the purpose of a compliance officer?

Which action should you take?

Choose only one option

To manage customer relationships

To make decisions regarding financial investments

To ensure adherence to regulatory requirements and internal policies

To oversee the performance of all departments

Question 2: What is the most critical element when preparing a stress test report for a financial institution?

Which action should you take?

Choose only one option

Forecasted market fluctuations

Sensitivity of the portfolio to adverse conditions

Stress scenarios in response to potential geopolitical risk

Comparison of real-time and historical financial data

Question 3: When assessing liquidity risk, which of the following data metrics is most useful in determining the ability of a financial institution to meet short-term obligations?

Which action should you take?

Choose only one option

Cash flow at risk (CFaR)

Current ratio

Net interest margin (NIM)

Debt-to-equity ratio

Question 4: How does a cash reserve act as a mitigation strategy for a bank's operational risk?

Which action should you take?

Choose only one option

It reduces the volatility in stock markets

It helps to increase profitability

It enables long-term investment without risk

It allows immediate liquidity to cover sudden losses

Question 5: In BFSI, what is the best approach to handle imbalanced datasets when predicting loan defaults?

Which action should you take?

Choose only one option

Oversampling minority class

Ignoring the imbalance

Removing majority class

Reducing dataset size

Question 6: What is the benefit of using a Bayesian network in risk modeling for financial institutions?

Which action should you take?

Choose only one option

It allows for the incorporation of prior knowledge and uncertainty in the risk modeling process

It increases the number of independent variables considered in the model

It reduces computational complexity in risk simulations

It eliminates the need for regularization in the model