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CMA Intermediate · Financial Management and Business Data Analytics · Receivable Management

In credit scoring of customers using a data analytics model, a logistic regression outputs a probability of default for each applicant. Which use of this output best supports a credit granting decision?

The probability of default should be compared against a cut-off chosen by weighing expected loss against expected contribution from the sale. Credit is granted where the risk is acceptable, which is how a logistic regression score supports credit granting decisions.

  1. AGrant credit to every applicant whose probability of default is below a cut-off set by comparing expected loss with expected contributionCorrect
  2. BGrant credit to all applicants since the model only measures averages
  3. CReject all applicants whose names appear earliest alphabetically
  4. DSet the credit period equal to the model's R-squared value in days

Explanation

A predicted default probability is used with a cut-off, balancing expected bad debt loss against the contribution from the sale. The other options ignore the model's purpose or use irrelevant criteria.

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