Temporally-Adaptive Linear Classification for Handling Population Drift in Credit Scoring

Niall M. Adams (), Dimitris K. Tasoulis (), Christoforos Anagnostopoulos () and David J. Hand ()
Additional contact information
Niall M. Adams: Imperial College London, Department of Mathematics
Dimitris K. Tasoulis: Imperial College London, Department of Mathematics
Christoforos Anagnostopoulos: Imperial College London, The Institute for Mathematical Sciences
David J. Hand: Imperial College London, Department of Mathematics

A chapter in Proceedings of COMPSTAT'2010, 2010, pp 167-176 from Springer

Abstract: Abstract Classification methods have proven effective for predicting the creditworthiness of credit applications. However, the tendency of the underlying populations to change over time, population drift, is a fundamental problem for such classifiers. The problem manifests as decreasing performance as the classifier ages and is typically handled by periodic classifier reconstruction. To maintain performance between rebuilds, we propose an adaptive and incremental linear classification rule that is updated on the arrival of new labeled data. We consider adapting this method to suit credit application classification and demonstrate, with real loan data, that the method outperforms static and periodically rebuilt linear classifiers.

Keywords: classification; credit scoring; population drift; forgetting factor (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2604-3_15

Ordering information: This item can be ordered from
http://www.springer.com/9783790826043

DOI: 10.1007/978-3-7908-2604-3_15

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().