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    Question

    In the context of risk modeling for credit scoring,

    which of the following factors is least likely to be used in predicting a person’s creditworthiness?
    A Employment history Correct Answer Incorrect Answer
    B Age Correct Answer Incorrect Answer
    C Income Correct Answer Incorrect Answer
    D Marital status Correct Answer Incorrect Answer
    E Credit utilization ratio Correct Answer Incorrect Answer

    Solution

    In risk modeling for credit scoring, the goal is to predict the likelihood of a person repaying a loan based on relevant financial behavior and personal information. Employment history, age, income, and credit utilization ratio are all direct indicators of financial stability, which is crucial for credit scoring. Employment history shows income stability, age could indicate experience or career maturity, income reflects the ability to repay, and the credit utilization ratio assesses how well an individual manages their available credit. Marital status, however, is not a strong predictor of creditworthiness in most cases, as it does not directly reflect an individual’s financial habits or capacity to repay debt. Therefore, while marital status might be considered in some cases for lifestyle or social profile segmentation, it is not typically a key factor in modeling credit scores. Why Other Options Are Incorrect: • A: Employment history is a key factor in credit scoring models as it reflects financial stability and the likelihood that the person has a steady income to meet financial obligations. • B: Age is often used to determine credit risk as it can correlate with experience in managing finances. People in certain age ranges (typically 25-50) may be considered to have more experience managing finances and may be less likely to default. • C: Income directly reflects an individual’s ability to repay debts, making it one of the most important variables in credit scoring models. • E: Credit utilization ratio is a direct measure of how much credit a person is using relative to their available credit limit, making it a critical factor in determining credit risk.

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