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An intelligent decision support system for credit card assessment based on a machine learning technique

Matsatsinis Nikolaos

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URIhttp://purl.tuc.gr/dl/dias/651F232B-6053-41C9-BE44-25C4FB159ECF-
Identifierhttps://doi.org/10.1007/BF02936329 -
Languageen-
Extent18 pagesen
TitleAn intelligent decision support system for credit card assessment based on a machine learning techniqueen
CreatorMatsatsinis Nikolaosen
CreatorΜατσατσινης Νικολαοςel
PublisherSpringer Verlagen
Content SummaryDuring the last two decades credit cards have became one of the main ways for accomplishing financial transactions. The number of credit card owners has increased rapidly. Unfortunately, at the same time the cases where the owners cannot fulfil their obligations to the banks have also been increased. This fact forced credit institutions and banks to search for methodologies that will allow them to accurately evaluate the credibility of each credit card applicant. Mullicriteria decision aid methods as well as machine learning algorithms can be used to accomplish this task. The present paper proposes a new intelligent decision support system for credit card evaluation, based on a machine learning algorithm, namely the Composite Rule Induction System. The major advantage of the algorithm and the system is the incorporation of qualitative variables which have an essential role in credit card evaluation. The system is applied on a real case study concerning credit card evaluation by a leading Greek commercial bank and the obtained results are compared to the results of a multicriteria decision aid method.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-04-
Date of Publication2002-
SubjectDecision Support Systemsen
SubjectCredit Cards Evaluationen
Bibliographic CitationN.F. Matsatsinis ," An intelligent decision support system for credit card assessment based on a machine learning technique," Oper.Research,vol. 2,no.2 ,pp. 243-260,Ma. 2002.doi:10.1007/BF02936329en

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