Title: Application of variable selection techniques to a modified SAIS for generating practical scorecards

Authors: Kevin Leung, France Cheong, Christopher Cheong, Sean O'Farrell, Robert Tissington

Addresses: School of Business Information Technology, Faculty of Business, RMIT University, Level 17, 239-251 Bourke Street, Melbourne, Victoria 3000, Australia. ' School of Business Information Technology, Faculty of Business, RMIT University, Level 17, 239-251 Bourke Street, Melbourne, Victoria 3000, Australia. ' School of Business Information Technology, Faculty of Business, RMIT University, Level 17, 239-251 Bourke Street, Melbourne, Victoria 3000, Australia. ' Retail Credit Risk, Asia, ANZ Banking Group Limited, Level 12 MCC Centre, 6778 Ayala Avenue, Makati, Philippines. ' Decision Model Design and Implementation, ANZ Banking Group Limited, Level 16, 100 Queen Street, Melbourne, Victoria 3000, Australia

Abstract: Selecting better predictive variables is fundamental for scorecards to perform well. This study makes use of a large credit scoring dataset and investigates the application of several variable selection techniques for scorecard development. The scorecards are developed using a statistical technique (logistic regression) and two AI methods (SAIS and AIRS). SAIS, which we previously developed can predict class outcomes accurately and has good classification accuracy which is the percentage of correctly classified data. However, since an unbalanced dataset was obtained, the Gini coefficient which is the main performance measure used in industry and which is insensitive to changes in class distribution needs be used instead. SAIS is modified to generate a Gini coefficient and an investigation of its suitability for practical scorecard development is made. We found that further modifications are needed in order for it to perform as well as logistic regression. Moreover, among the different variable selection techniques used, stepwise regression was found to perform best.

Keywords: variable selection; artificial immune recognition system; AIRS; credit scoring; scorecards; logistic regression; Gini coefficient; stepwise regression; performance measures; financial risk management; simple artificial intelligence system; SAIS.

DOI: 10.1504/IJADS.2009.027930

International Journal of Applied Decision Sciences, 2009 Vol.2 No.3, pp.233 - 261

Available online: 20 Aug 2009 *

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