Pavlidis, N. and Tasoulis, Dimitrios and Adams, N. M. and Hand, D. J. (2012) Adaptive consumer credit classification. Journal of the Operational Research Society, 63 (12). pp. 1645-1654. ISSN 1476-9360Full text not available from this repository.
Credit scoring methods for predicting creditworthiness have proven very effective in consumer finance. In light of the present financial crisis, such methods will become even more important. One of the outstanding issues in credit risk classification is population drift. This term refers to changes occurring in the population due to unexpected changes in economic conditions and other factors. In this paper, we propose a novel methodology for the classification of credit applications that has the potential to adapt to population drift as it occurs. This provides the opportunity to update the credit risk classifier as new labelled data arrives. Assorted experimental results suggest that the proposed method has the potential to yield significant performance improvement over standard approaches, without sacrificing the classifier's descriptive capabilities.
|Journal or Publication Title:||Journal of the Operational Research Society|
|Uncontrolled Keywords:||credit scoring ; logistic regression ; population drift ; online learning ; H-measure|
|Subjects:||H Social Sciences > HB Economic Theory|
|Departments:||Lancaster University Management School > Management Science|
|Deposited On:||09 Mar 2012 09:01|
|Last Modified:||17 Jun 2016 01:14|
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