The scope of this study is to investigate the capability of AI methods to accurately detect and predict credit risks based on retail borrowers' features. The comparison of logistic regression, decision tree, and random forest showed that machine learning methods are able to predict credit...

The use of credit ratings has been advocated by regulators in the US as well as in Europe. The creation of “Nationally Recognized Statistical Rating Organizations” statue strengthened the appearance of the triopoly of Moody's, Standard & Poor's and Fitch thus creating a de jure dominant...

A retail bank consumer loan dataset is used to develop logistic regression based scoring functions with different definitions of default from a very broad to a narrow or hard. The performance of the scoring functions is compared with respect to the hard definition of default which indicates real...

With the New Basle Capital Accord banks' capital requirements are determined with risk weights based on internal and external ratings and probabilities of default (PD's). PD's are mostly estimated from historical default rates. In recent working papers the Basle Committee on Banking Supervision...