A Comparison of Variable Selection Techniques for Credit Scoring

Selecting new and more predictive variables is fundamental for scorecards to perform well. This study makes use of a very large set of credit scoring data and investigates the application of several variable selection techniques for scorecard development. Among the four different techniques used, stepwise regression, which is currently the most popular technique used in practice, was found to perform best.