IJERT-EMS
IJERT-EMS

Credit Card Fraud Detection Using Hidden Markov Model


Credit Card Fraud Detection Using Hidden Markov Model
Authors : SIVA PARVATHI.NELLURI, SHAIK. NAGUL , Dr .M.KISHOREKUMAR
Publication Date: 03-08-2012

Authors

Author(s):  SIVA PARVATHI.NELLURI, SHAIK. NAGUL , Dr .M.KISHOREKUMAR

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Vol.1 - Issue 5 (July - 2012)

e-ISSN:   2278-0181

Abstract

Abstract?Due to a rapid advancement in the electronic commerce technology, the use of credit cards has dramatically increased. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising. In this paper, we model the sequence of operations in credit card transaction processing using a Hidden Markov Model (HMM) and show how it can be used for the detection of frauds. An HMM is initially trained with the normal behavior of a cardholder. If an incoming credit card transaction is not accepted by the trained HMM with sufficiently high probability, it is considered to be fraudulent. At the same time, we try to ensure that genuine transactions are not rejected. We present detailed experimental results to show the effectiveness of our approach and compare it with other techniques available in the literature.

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