A comparison of data mining techniques for credit scoring in banking: A managerial perspective

dc.contributor.author	Ince, H.
dc.contributor.author	Aktan, B.
dc.date.accessioned	2021-01-25T20:51:48Z
dc.date.available	2021-01-25T20:51:48Z
dc.date.issued	2009
dc.identifier	10.3846/1611-1699.2009.10.233-240
dc.identifier.issn	16111699
dc.identifier.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-75449093022&doi=10.3846%2f1611-1699.2009.10.233-240&partnerID=40&md5=9374e49427cc3c348b6b99be1d4e7066
dc.identifier.uri	https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/10704
dc.description.abstract	Credit scoring is a very important task for lenders to evaluate the loan applications they receive from consumers as well as for insurance companies, which use scoring systems today to evaluate new policyholders and the risks these prospective customers m
dc.language.iso	English
dc.publisher	Journal of Business Economics and Management
dc.title	A comparison of data mining techniques for credit scoring in banking: A managerial perspective
dc.type	Article
dc.relation.firstpage	233
dc.relation.lastpage	240
dc.relation.volume	10
dc.relation.issue	3
dc.description.affiliations	Gebze Institute of Technology, Kocaeli, Turkey; Yasar University, Izmir, Turkey; University of Primorska, Slovenia

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