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Create Credit Scorecards

Credit scorecard modeling, binning, fitting a model, obtaining points and scores, model validation, probability of default, create compact scorecard

For information about the workflow for developing credit scorecards, see Credit Scorecard Modeling Workflow. Additional tools for working with credit scorecards are available in Risk Management Toolbox™. For more information, see Consumer Credit Risk (Risk Management Toolbox).


creditscorecardCreate creditscorecard object to build credit scorecard model


autobinningPerform automatic binning of given predictors
bininfoReturn predictor’s bin information
predictorinfoSummary of credit scorecard predictor properties
fillmissingReplace missing values for credit scorecard predictors (Since R2020a)
modifybinsModify predictor’s bins
modifypredictorSet properties of credit scorecard predictors
bindataBinned predictor variables
plotbinsPlot histogram counts for predictor variables
fitmodelFit logistic regression model to Weight of Evidence (WOE) data
fitConstrainedModelFit logistic regression model to Weight of Evidence (WOE) data subject to constraints on model coefficients (Since R2019a)
setmodelSet model predictors and coefficients
displaypointsReturn points per predictor per bin
formatpointsFormat scorecard points and scaling
scoreCompute credit scores for given data
probdefaultLikelihood of default for given data set
validatemodelValidate quality of credit scorecard model
screenpredictorsScreen credit scorecard predictors for predictive value (Since R2019a)
compactCreate compact credit scorecard (Since R2019a)

Live Editor Tasks

Thresholds for Screen Predictors Select thresholds for predictor risk metrics in the Live Editor (Since R2021b)

Examples and How To



Troubleshooting Credit Scorecard Results

Troubleshoot results when using a creditscorecard model.