Credit Granting: A Comparative Analysis of Classification Procedures
比较了参数、非参数和判断性分类方法在公司信贷数据上的效果，发现非参数递归分割法信息量更大，判断性模型与统计模型表现相当，并提出两者互补的信贷审批范式。
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.