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Adaptive consumer credit classification

Research output: Contribution to Journal/MagazineJournal articlepeer-review

<mark>Journal publication date</mark>12/2012
<mark>Journal</mark>Journal of the Operational Research Society
Issue number12
Number of pages10
Pages (from-to)1645-1654
Publication StatusPublished
Early online date29/02/12
<mark>Original language</mark>English


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.