Credit Granting: A Comparative Analysis of Classification Procedures

Authors

  • VENKAT SRINIVASAN,

  • YONG H. KIM

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    • Northeastern University and University of Cincinnati, respectively. We are grateful to Robert Eisenbeis and Sangit Chatterjee for their insightful comments on an earlier draft. We also thank an anonymous Fortune 500 corporation as well as the Credit Research Foundation for their support. The usual disclaimer applies.

ABSTRACT

Financial classification issues, and particularly the financial distress problem, continue to be subject to vigorous investigation. The corporate credit granting process has not received as much attention in the literature. This paper examines the relative effectiveness of parametric, nonparametric and judgemental classification procedures on a sample of corporate credit data. The judgemental model is based on the Analytic Hierarchy Process. Evidence indicates that (nonparametric) recursive partitioning methods provide greater information than simultaneous partitioning procedures. The judgemental model is found to perform as well as statistical models. A complementary relationship is proposed between the statistical and the judgemental models as an effective paradigm for granting credit.

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