Credit Card Fraud Detection Using Hidden Markov Model
Shailesh S. Dhok
Shailesh S. Dhok, ME(Scholar), University- Sant Gadge Baba Amravati University, College-P.R.M.I.T & R, Badnera, City-Amravati, Country-India.
Manuscript received on January 30, 2012. | Revised Manuscript received on February 03, 2012. | Manuscript published on March 05, 2012. | PP: 88-92 | Volume-2 Issue-1, March 2012. | Retrieval Number: A0385012111 /2012©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The most accepted payment mode is credit card for both online and offline in today’s world, it provides cashless shopping at every shop in all countries. It will be the most convenient way to do online shopping, paying bills etc. Hence, risks of fraud transaction using credit card has also been increasing. In the existing credit card fraud detection business processing system, fraudulent transaction will be detected after transaction is done. It is difficult to find out fraudulent and regarding loses will be barred by issuing authorities. Hidden Markov Model is the statistical tools for engineer and scientists to solve various problems. In this paper, it is shown that credit card fraud can be detected using Hidden Markov Model during transactions. Hidden Markov Model helps to obtain a high fraud coverage combined with a low false alarm rate.
Keywords: Internet, online shopping, credit card, e-commerce security, fraud detection, Hidden Markov Model.