Revista de Economía y Negocios

Modeling Banks’ Probability of Default

Abstract

Xiaoming Tong

The unprecedented financial crisis of 2008-2009 has called attention to limitations of existing methods for estimating the default risk of financial intuitions. To address this need, I built and tested a time-adaptive statistical model that predicts the default probabilities of banks. The model inputs are a set of financial ratios suggested in the literature, and subsequently verified, to be effective in forecasting future bank failures. The model provides estimates of banks’ cumulative default probability profiles from one to thirty years out, albeit with decreasing accuracy. The model was validated through out-of-sample testing regarding its ability to accurately predict the defaults of U.S. depository institutions between 1992 and 2012. This method provides out-of-sample testing as well as best mimics how the model will be used in practice. The model performed well at separating potential defaulting banks from nondefaults over one-year horizons. Although performance drops monotonically when predicting defaults over longer horizons, the model performs significantly above chance for time periods as long as five years from the scoring date.