Economics and Finance Literature: Historical Perspective
The quantitative credit analysis literature began with Altman (1968), where the author proposes discriminant analysis to determine combinations of observable characteristics that may best differentiate between defaulted and non-defaulted firms. This paper was one of the first examples of a quantitative, “credit-scoring” approach to credit assessment. This approach has fallen out of favor in recent decades, in part because of the descriptive focus. Discriminant analysis characterizes a firm’s likely observable characteristics given the current default status, while a credit analyst is generally interested in the converse: a firm’s likely default status given its observable characteristics. In addition to this point, Lo (1986) proves that discriminant analysis is consistent in a much more limited set of circumstances relative to other, more modern approaches. One such approach is logistic regression models that afford a methodology to estimate directly the effects of particular variables on default probabilities (or in the case of logistic regression, the log odds-ratios of the default probabilities).