Other Credit Risk Models
In Chapters 4 and 5, we describe the two developing branches of academic work in credit risk modeling: structural models and reduced form models. In this chapter, we describe other, more established models, whose inceptions date back several decades. These models have proven their usefulness over the long run and continue to be used and improved as new modeling developments are incorporated into the fundamental models. We describe:
• Credit scoring systems, such as the Altman Z score model.
• Mortality rate systems, following the insurance industry’s approach.
• Neural network systems.
Upon completing our survey of default probability estimation models, we undertake a broad comparison of their accuracy.
CREDIT SCORING SYSTEMS
Credit scoring systems can be found in virtually all types of credit analysis, from consumer credit to commercial loans. The idea is to identify certain key factors that determine the probability of default (as opposed to repayment), and combine or weight them into a quantitative score. In some cases, the score can be literally interpreted as a probability of default; in others, the score can be used as a classification system. That is, it places a potential borrower into either a good or a bad group, based on a score and a cutoff point. Full reviews of the traditional approach to credit scoring, and the various methodologies, can be found in Caouette, Altman, and Narayanan (1998). A good review of the worldwide ...