Are Credit Scoring Models Sensitive With Respect to Default Definitions? Evidence from the Austrian Market
by Evelyn Hayden of the University of Vienna
Abstract: In this paper models of default prediction conditional on financial statements of Austrian firms are presented. Apart from giving a discussion on the suggested 65 variables the issue of potential problems in developing rating models is raised and possible solutions are reviewed. A unique data set on credit risk analysis for the Austrian market is constructed and used to derive rating models for three different default definitions, i.e. bankruptcy, restructuring, and delay-in-payment. The models are compared to examine whether the models developed on the tighter default criteria, that are closer to the definition proposed by Basel II, do better in predicting these credit loss events than the model estimated on the traditional and more easily observable default criterion bankruptcy. Several traditional methods to compare rating models are used, but also a rigorous statistical test is discussed and applied. All results lead to the same conclusion that not much prediction power is lost if the bankruptcy model is used to predict the credit loss events of rescheduling and delay-in-payment instead of the alternative models specifically derived for these default definitions. In the light of Basel II this is an interesting result. It implies that traditional credit rating models developed by banks by exclusively relying on bankruptcy as default criterion are not automatically outdated but can be equally powerful in predicting the comprising credit loss events provided in the new Basel capital accord as models estimated on these default criteria.