Credit scoring via PCALWM

  • Authors:

  • Jianping Li;Weixuan Xu;Yong Shi

  • Affiliations:

  • Institute of Policy and Management, Chinese Academy of Sciences, Beijing, P.R.China;Institute of Policy and Management, Chinese Academy of Sciences, Beijing, P.R.China;Research Center on Data Technology and Knowledge Economy, Chinese Academy of Sciences, Beijing, P.R.China

  • Venue:
  • ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part III
  • Year:
  • 2005

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Abstract

We have presented a principal component analysis linear-weighted model (PCALWM) for credit scoring in [5,6], this article is a further study on this model. We revised the application procedure in the credit scoring, and tested it by a larger real-life credit card dataset. In comparison with some well-known scores, the empirical results of the PCALWM can achieve a favorable KS distance. The study on some application features of this model in the credit decision-making shows that the model can help the credit issuers to select the best trade-off among the enterprise stratagem, marketing and credit risk management.