Behavioral Scorecards for Existing Customers: Build, Validate, and Monitor Monthly Risk Scores
A practical guide to behavioral scorecard design for existing accounts: point-in-time data, 12-month outcomes, PD calibration, validation, and monitoring.
Credit risk topic
Credit scorecards
Build, scale, validate, and monitor application and behavioural scorecards.
Guides and worked examples
Credit Scorecard Scaling: Convert Points to Odds and Probability of Default
Derive a points-to-double-odds scale from a chosen anchor, convert score points to good-to-bad odds and PD, work a synthetic example, and monitor whether the PD mapping remains calibrated.
How to Calculate Predictor Weights in Logistic Regression: Coefficients, Contributions, and Scorecard Points
Learn what logistic-regression coefficients mean, how to convert coefficient × sample standard deviation into percentage weights summing to 100%, and how coefficients become scorecard points using a worked synthetic PD example.
A credit scorecard development blueprint
Design the sample, target, predictors, score scale, validation, and decision use as one workflow.
Binning, Weight of Evidence, and Information Value
Calculate bin-level evidence while guarding against unstable or empty bins.
Logistic regression and score scaling
Translate model log-odds into probabilities and a points scale with visible conventions.
Cut-offs, overrides, and reject inference
Choose operational thresholds with evidence and document what rejected applications conceal.