An Examination of the Conceptual Issues Involved in Developing Credit-Scoring Models
考察了多元判别分析在信用评分模型中的理论要求，指出模型假设不满足时会产生偏差，并认为理解模型局限性比严格满足假设更重要。
Abstract Multiple discriminant analysis (MDA) is frequently used to develop statistical credit-scoring models for loan evaluation purposes. Current legislative efforts to insure that credit is being granted in a nondiscriminatory manner have focused considerable attention on the reliability of such models. This article examines the theoretical requirements of the MDA model in the context of a realistic lending situation and illustrates the extent of bias when these theoretical assumptions are not fully met. The article concludes that failure to rigorously meet all the theoretical assumptions of the statistical model may not be as critical as insuring that credit managers fully understand the limitations of these types of decision tools. Furthermore, the evidence indicates that statistical models other than multiple discriminant analysis are possibly more relevant to the credit-granting decision. KEY WORDS: DiscriminantScoringLending