Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Development of educational software for coarse classifying and model evaluation in credit scoring

개인신용평점에서 항목그룹화와 모형평가를 위한 교육용 소프트웨어의 개발

  • Jung, Ki-Mun (Department of Informational Statistics, Kyungsung University)
  • 정기문 (경성대학교 정보통계학과)
  • Received : 2010.09.28
  • Accepted : 2010.11.22
  • Published : 2010.11.30
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Abstract

The coarse classifying procedure in credit scoring splits the values of a continuous characteristic into bands and the values of a discrete characteristic into groups of values. Also, the scorecard degrades over time and thus we should adjust the cut-off score being used. However, the coarse classifying and the adjustment of cut-off score in credit scoring are very complicate and troublesome procedure. Thus, in this paper, we develop a software for the coarse classifying and the model evaluation by using Visual Basic Language. By using the developed software, we can find the best split in the coarse classifying and the optimal cut-off score in the model evaluation.

개인신용평점에서 항목그룹화의 과정은 연속형 특성변수를 밴드로 분할하고 이산형 특성변수는 그룹으로 분할하는 것이다. 또한 평점표는 시간이 지나감에 따라 성능이 떨어지게 되고, 따라서 사용되고 있는 승인점을 조정하여야 한다. 그러나 개인신용평점에서 항목그룹화와 승인점의 조정은 매우 복잡하고 번거로운 과정이라고 할 수 있다. 따라서 본 논문에서는 비주얼베이직을 사용하여 개인신용평점에서 항목그룹화와 모형평가를 위한 소프트웨어를 개발하였다. 개발된 소프트웨어를 활용하면 항목그룹화에서 최적의 분할과 모형평가에서 최적의 승인점을 쉽게 찾을 수 있다.

Keywords

References

  1. Choi, H. S. (2006a). A program for teaching Type I and Type II errors. Journal of the Korean Data & Information Science Society, 17, 19-30.
  2. Choi, H. S. (2006b). The teaching of statistics using Excel VBA. Journal of the Korean Data & Information Science Society, 17, 811-820.
  3. Choi, H. S. and Kim, T. Y. (2005). Computer simulation program for central limit theorem. Journal of the Korean Data & Information Science Society, 16, 359-369.
  4. Jung, K. M., Kim, M. C. and Yum, J. K. (2006). Development of software for coarse classifying. Journal of the Korean Data & Information Science Society, 17, 1085-1090.
  5. Thomas, L. C. (2000). A Survey of Credit and behavioral scoring: Forecasting financial risk of lending to consumers. International Journal of Forecasting, 16, 149-172. https://doi.org/10.1016/S0169-2070(00)00034-0
  6. Thomas, L. C. (2009). Consumer credit models: pricing, profit and portfolios, Oxford University Press, Oxford.
  7. Thomas, L. C., Edelman D. B. and Crook, J. N. (2002). Credit scoring and its application, SIAM.
  8. Thomas, L. C. and Jung, K. M. (2010). When to rebuild and when to recalibrate credit scorecards. 24th European Conference on Operational research.