Bump hunting for risk: A new data mining tool and its applications

Bump Hunting is a new data mining technique. In this paper we explore its potential for risk assessment. The method is first presented and illustrated by application to credit risk data from a German bank. Based on comparisons with standard analyses of this data set, we conclude that Bump Hunting has potential for identification of risk in financial applications. In the next step the original Bump Hunting algorithm is modified for analysis of censored survival data. This Survival Bump Hunting is used for the analysis of a bone marrow transplant data set and these results are compared to previous analyses which used standard survival methods such as Cox regression. The findings obtained using Survival Bump Hunting confirmed the previous analyses and added some interesting new aspects.