Abstract

In modern retail market environment, electronic commerce has rapidly gained a lot of attention and also provides instantaneous transactions. In electronic commerce, credit card has become the most important means of payment due to fast development in information technology around the world. As the usage of credit card increases in the last decade, rate of fraudulent practices is also increasing every year. Existing fraud detection system may not be so much capable to reduce fraud transaction rate. Improvement in fraud detection practices has become essential to maintain existence of payment system. In this paper, we show how Hidden Markov Model (HMM) is used to detect credit card fraud transaction with low false alarm. An HMM based system is initially studied spending profile of the card holder and followed by checking an incoming transaction against spending behavior of the card holder, if it is not accepted by our proposed HMM with sufficient probability, then it would be a fraudulent transaction.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.