Development and application of consumer credit scoring models using profit-based V classification measures

datacite.alternateIdentifier.issn0377-2217
datacite.creatorVerbraken, T.
datacite.creatorBravo, C.
datacite.creatorWeber, R.
datacite.creatorBaesens, B.
datacite.date.issued2014-10-16
datacite.subjectData analyticsen_US
datacite.subjectCutoff pointen_US
datacite.subjectPerformance measurementen_US
datacite.subjectClassificationen_US
datacite.subjectCredit scoringen_US
datacite.titleDevelopment and application of consumer credit scoring models using profit-based V classification measuresen_US
dc.date.accessioned2014-11-21T21:12:18Z
dc.date.available2014-11-21T21:12:18Z
dc.descriptionGomez, C (Gomez, Carlos); Bravo, C (Bravo, Cristian) Univ Talca, Dept Modelamiento & Gest Ind, Curico, Chileen_US
dc.description.abstractThis paper presents a new approach for consumer credit scoring, by tailoring a profit-based classification performance measure to credit risk modeling. This performance measure takes into account the expected profits and losses of credit granting and thereby better aligns the model developers' objectives with those of the lending company. It is based on the Expected Maximum Profit (EMP) measure and is used to find a trade-off between the expected losses - driven by the exposure of the loan and the loss given default and the operational income given by the loan. Additionally, one of the major advantages of using the proposed measure is that it permits to calculate the optimal cutoff value, which is necessary for model implementation. To test the proposed approach, we use a dataset of loans granted by a government institution, and benchmarked the accuracy and monetary gain of using EMP, accuracy, and the area under the ROC curve as measures for selecting model parameters, and for determining the respective cutoff values. The results show that our proposed profit-based classification measure outperforms the alternative approaches in terms of both accuracy and monetary value in the test set, and that it facilitates model deployment. (C) 2014 Elsevier B.V. All rights reserved.en_US
dc.identifier.citationEUROPEAN JOURNAL OF OPERATIONAL RESEARCH 238 (2) : 505-513en_US
dc.identifier.urihttps://repositorio.utalca.cl/repositorio/handle/1950/10060
dc.languageenen_US
dc.publisherELSEVIER SCIENCE BVen_US
oaire.resourceTypeArtículoen_US
utalca.indexArtículo de publicación ISI
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
TEXTO_COMPLETO.html
Size:
3.08 KB
Format:
Hypertext Markup Language
Description:
DESCARGAR
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.8 KB
Format:
Item-specific license agreed upon to submission
Description: