On the suitability of resampling techniques for the class imbalance problem in credit scoring

A I Marqués, V García and J S Sánchez
Additional contact information
A I Marqués: Universitat Jaume I, Castellón, Spain
V García: Universitat Jaume I, Castellón, Spain
J S Sánchez: Universitat Jaume I, Castellón, Spain

Journal of the Operational Research Society, 2013, vol. 64, issue 7, 1060-1070

Abstract: In real-life credit scoring applications, the case in which the class of defaulters is under-represented in comparison with the class of non-defaulters is a very common situation, but it has still received little attention. The present paper investigates the suitability and performance of several resampling techniques when applied in conjunction with statistical and artificial intelligence prediction models over five real-world credit data sets, which have artificially been modified to derive different imbalance ratios (proportion of defaulters and non-defaulters examples). Experimental results demonstrate that the use of resampling methods consistently improves the performance given by the original imbalanced data. Besides, it is also important to note that in general, over-sampling techniques perform better than any under-sampling approach.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.palgrave-journals.com/jors/journal/v64/n7/pdf/jors2012120a.pdf Link to full text PDF (application/pdf)
http://www.palgrave-journals.com/jors/journal/v64/n7/full/jors2012120a.html Link to full text HTML (text/html)
Access to full text is restricted to subscribers.

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:pal:jorsoc:v:64:y:2013:i:7:p:1060-1070

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook

More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().