A self tuning model for risk estimation

Abstract

Credit scoring models often use linear or logistic regression to investigate the relation between observed characteristics and credit ratings. The basic relation is, however, a form of Bayes' theorem. This paper proposes a model in which estimation techniques from hidden Markov models are adapted to evaluate the parameters of a risk profile. The risk being estimated might be financial, as in credit scoring, or alternatively whether an observed member of a population might represent some terrorist threat. © 2007 Elsevier Ltd. All rights reserved.