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Reseach Article

Investigation of Data Mining Techniques in Fraud Detection: Credit Card

by R. Gayathri, A. Malathi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 82 - Number 9
Year of Publication: 2013
Authors: R. Gayathri, A. Malathi
10.5120/14143-1560

R. Gayathri, A. Malathi . Investigation of Data Mining Techniques in Fraud Detection: Credit Card. International Journal of Computer Applications. 82, 9 ( November 2013), 12-15. DOI=10.5120/14143-1560

@article{ 10.5120/14143-1560,
author = { R. Gayathri, A. Malathi },
title = { Investigation of Data Mining Techniques in Fraud Detection: Credit Card },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 82 },
number = { 9 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume82/number9/14143-1560/ },
doi = { 10.5120/14143-1560 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:57:48.837586+05:30
%A R. Gayathri
%A A. Malathi
%T Investigation of Data Mining Techniques in Fraud Detection: Credit Card
%J International Journal of Computer Applications
%@ 0975-8887
%V 82
%N 9
%P 12-15
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent times the more secure data transfer takes place almost by means of internet. Apart from the corporate companies, publics also started using the network media. At the same time the risk also increases in secure data transfer. One of the major issue among them is credit card fraud detection systems which has a significant percentage of transactions labeled as fraudulent are in fact legitimate. Thus this may delay the fraudulent transaction detection. Due to ever increasing volumes of data needed to be analyzed using data mining methods and techniques which are being used more and more. The aim of this study is to analyze the five most frequently used classification techniques in fraudulent detection. Neural Network, Decision Tree, Naïve Bayes, K-nn and Support Vector Machine are taken in to consideration. This paper discusses on each techniques and their limitations. Still they suffer from the problem of false detection rate highly.

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Index Terms

Computer Science
Information Sciences

Keywords

Neural Networks Decision Tree Support Vector Machines Credit Card Fraud Detection