Skip to content

FRM Part II · FRM Exam Part II · Credit Scoring and Rating

A retail lender builds a logistic regression scorecard to predict 12-month default on personal loans. Each predictor is first grouped into bins, and each bin is assigned a value based on the log of the ratio of the proportion of non-defaulters to the proportion of defaulters in that bin. Which term describes this bin value?

The bin value is the weight of evidence, calculated as the natural log of the proportion of good accounts divided by the proportion of bad accounts in the bin. It converts grouped predictors into risk-ordered inputs for a logistic scorecard, unlike Gini, KS or PSI, which assess performance or stability.

  1. AWeight of evidenceCorrect
  2. BGini coefficient
  3. CPopulation stability index
  4. DKolmogorov-Smirnov statistic

Explanation

Weight of evidence for a bin is ln(% good / % bad). It transforms a binned variable into a monotonic risk measure for the logistic model. Gini, PSI and KS are performance or stability metrics, not bin values.

Did you get it right without looking?

One question tells you little. A timed set on Credit Scoring and Rating shows your real accuracy, how long you take and where you lose marks.

Practise Credit Scoring and RatingFree diagnostic mock

More Credit Scoring and Rating questions