Publication:
Detecting credit card fraud by ANN and logistic regression

dc.contributor.authorsSahin Y., Duman E.
dc.date.accessioned2022-03-15T01:58:44Z
dc.date.accessioned2026-01-11T13:18:44Z
dc.date.available2022-03-15T01:58:44Z
dc.date.issued2011
dc.description.abstractWith the developments in information technology and improvements in communication channels, fraud is spreading all over the world, resulting in huge financial losses. Though fraud prevention mechanisms such as CHIP&PIN are developed, these mechanisms do not prevent the most common fraud types such as fraudulent credit card usages over virtual POS terminals through Internet or mail orders. As a result, fraud detection is the essential tool and probably the best way to stop such fraud types. In this study, classification models based on Artificial Neural Networks (ANN) and Logistic Regression (LR) are developed and applied on credit card fraud detection problem. This study is one of the firsts to compare the performance of ANN and LR methods in credit card fraud detection with a real data set. © 2011 IEEE.
dc.identifier.doi10.1109/INISTA.2011.5946108
dc.identifier.isbn9781612849195
dc.identifier.urihttps://hdl.handle.net/11424/247109
dc.language.isoeng
dc.relation.ispartofINISTA 2011 - 2011 International Symposium on INnovations in Intelligent SysTems and Applications
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectANN
dc.subjectclassification
dc.subjectCredit card fraud detection
dc.subjectlogistic regression
dc.titleDetecting credit card fraud by ANN and logistic regression
dc.typeconferenceObject
dspace.entity.typePublication
oaire.citation.endPage319
oaire.citation.startPage315
oaire.citation.titleINISTA 2011 - 2011 International Symposium on INnovations in Intelligent SysTems and Applications

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