IE interfaces (산업공학)

Korean Institute of Industrial Engineers (대한산업공학회)
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SVM based Bankruptcy Prediction Model for Small & Micro Businesses Using Credit Card Sales Information

신용카드 매출정보를 이용한 SVM 기반 소상공인 부실예측모형

  • Yoon, Jong-Sik (Department of Industrial & Systems Engineering, Dongguk Univ.) ;
  • Kwon, Young-Sik (Department of Industrial & Systems Engineering, Dongguk Univ.) ;
  • Roh, Tae-Hyup (Department of Business Management, Seoul Women's Univ.)
  • 윤종식 (동국대학교 산업시스템공학과) ;
  • 권영식 (동국대학교 산업시스템공학과) ;
  • 노태협 (서울여자대학교 경영학과)
  • Received : 20070100
  • Accepted : 20070300
  • Published : 2007.12.31
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Abstract

The small & micro business has the characteristics of both consumer credit risk and business credit risk. In predicting the bankruptcy for small-micro businesses, the problem is that in most cases, the financial data for evaluating business credit risks of small & micro businesses are not available. To alleviate such problem, we propose a bankruptcy prediction mechanism using the credit card sales information available, because most small businesses are member store of some credit card issuers, which is the main purpose of this study. In order to perform this study, we derive some variables and analyze the relationship between good and bad signs. We employ the new statistical learning technique, support vector machines (SVM) as a classifier. We use grid search technique to find out better parameter for SVM. The experimental result shows that credit card sales information could be a good substitute for the financial data for evaluating business credit risk in predicting the bankruptcy for small-micro businesses. In addition, we also find out that SVM performs best, when compared with other classifiers such as neural networks, CART, C5.0 multivariate discriminant analysis (MDA), and logistic regression.

Keywords

References

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