Journal of the Operational Research Society

, Volume 63, Issue 12, pp 1645–1654

Adaptive consumer credit classification

General Paper

Abstract

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.

Keywords

credit scoring logistic regression population drift online learning H-measure 

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Copyright information

© Operational Research Society 2012

Authors and Affiliations

  • N G Pavlidis
    • 1
  • D K Tasoulis
    • 2
  • N M Adams
    • 3
  • D J Hand
    • 2
    • 3
  1. 1.Lancaster UniversityLancasterUK
  2. 2.Winton Capital ManagementLondonUK
  3. 3.Imperial College of Science, Technology and MedicineLondonUK

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