Preview Questions Credit Analyst | Role Specific Skill

Question 1: What is the role of credit rating migration in credit risk modeling?

Which action should you take?

Choose only one option

To compute loss given default

To validate external credit reports

To assess changes in creditworthiness over time

To track the borrower's payment history

Question 2: When assessing "Credit Scoring Models," how do you weigh the significance of credit history versus current financial behavior?

Which action should you take?

Choose only one option

I prioritize recent financial behavior (e.g., payment history, credit utilization) as it is a more accurate reflection of current creditworthiness

I treat both equally, as long as both the history and behavior are positive

I rely more heavily on the borrower's long-term credit history

I focus solely on current financial behavior and disregard the credit history

Question 3: In market research for credit analysis, why is it critical to consider the cyclical nature of industries such as manufacturing or real estate?

Which action should you take?

Choose only one option

It alters the company's market share over time

It affects cash flow projections and default likelihood

It influences loan term structuring

It has no effect on credit risk assessment

Question 4: Which model is most suitable for predicting the probability of default (PD) for corporate borrowers?

Which action should you take?

Choose only one option

K-Nearest Neighbors

Logistic Regression

Support Vector Machines

Decision Trees

Question 5: Why is trend analysis critical when studying industry credit risk?

Which action should you take?

Choose only one option

Simplifies financial modeling

Identifies cyclic patterns

Reduces operational risks

Provides short-term recovery forecasts

Question 6: What is the significance of "decile analysis" in credit scoring model performance evaluation?

Which action should you take?

Choose only one option

It ranks borrowers based on their financial statements

It identifies the top ten% of borrowers most likely to default

It groups borrowers into ten equal-sized segments based on their credit scores and evaluates performance within each decile

It measures the correlation between different predictor variables