Credit card fraud detection using Hidden Markov Model

Since past few years there is tremendous advancement in electronic commerce technology, and 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 present the necessary theory to detect fraud in credit card transaction processing using a Hidden Markov Model (HMM). 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 by using an enhancement to it(Hybrid model).In further sections we compare different methods for fraud detection and prove that why HMM is more preferred method than other methods.