Failure Prediction Models: Performance, Disagreements, and Internal Rating Systems

Abstract

We address a number of comparative issues relating to the performance of failure prediction models for small, private firms. We use two models provided by vendors, a model developed by the National Bank of Belgium, and the Altman Z-score model to investigate model power, the extent of disagreement between models in the ranking of firms, and the design of internal rating systems. We also examine the potential gains from combining the output of multiple models. We find that the power of all four models in predicting bankruptcies is very good at the one-year horizon, even though not all of the models were developed using bankruptcy data and the models use different statistical methodologies. Disagreements in firm rankings are nevertheless significant across models, and model choice will have an impact on loan pricing and origination decisions. We find that it is possible to realize important gains from combining models with similar power. In addition, we show that it can also be beneficial to combine a weaker model with a stronger one if disagreements across models with respect to failing firms are high enough. Finally, the number of classes in an internal rating system appears to be more important than the distribution of borrowers across classes.

Bank Competition and Collateral: Theory and Evidence

“…4 In Hauswald and Marquez (2006), the quality of the screening signal depends on the distance between banks and borrowers as well. Empirical evidence also shows that different banks rate obtain different results from screening a particular borrower (Jacobson, Lindé and Roszbach, 2006;Mitchell and van Roy, 2007). This is consistent with our setup.…”

A hybrid bankruptcy prediction model with dynamic loadings on accounting-ratio-based and market-based information: A binary quantile regression approach

“…In particular, most closely related is the research by Miller (1998), Kealhofer and Kurbat (2001), Kealhofer (2003), Löffler (2007) and Mitchell and Roy (2008). Except for the findings of Kealhofer and Kurbat (2001), these studies conclude that combining various failure prediction models improves the prediction of default over the use of a single measure.…”

“…Even if one model is superior to the other, it does not imply that the inferior model should be neglected altogether. It may be possible to combine the two models to form an even better one (see Miller, 1998;Kealhofer and Kurbat, 2001;Kealhofer, 2003;Löffler, 2007;Mitchell and Roy, 2008). This study claims that both accounting-ratio-based and market-based information should be valuable for bankruptcy prediction.…”

Ścieżki niepowodzeń gospodarczych. Redukcja zagrożenia niepowodzeniem jako element strategii małej firmy

“…Banki coraz uważniej zaczęły się przyglądać zdolności kredytobiorców do spłaty kredytów, a bankowe oceny ryzyka kredytowego coraz częściej uwzględniają specyfikę danego kredytobiorcy (por. teżMitchell, van Roy 2007). Z tego powodu banki, dokonując analizy ryzyka kredytowego, potrzebują informacji o szerszym zakresie (czynniki ilościowe i jakościowe).…”