Bayesian approach to model credit risk

Credit risk is an especially tough modelling problem due to biased data and big time lags between training and model performance data. In this context a Bayesian approach seems particularly fit. We describe an implementation and compare results from a classical modelling approach and the Bayesian approach for a big ( >1 MM ) client data base for several years