Credit Card Fraud Detection Using Hidden Markov Model and Naive Bayes
In the past few years uses of electronic commerce technology and credit card has increased dramatically. As a credit card becomes the most popular way of paying there are cases of fraud associated with regular purchases. An HMM is initially trained with the usual behavior of a cardholder. If someone's Credit card transactions are not accepted by trained HMM With sufficiently high probability, it is considered Fraudulent. At the same time, we try to ensure that the real Transaction is not denied using (hybrid model).In this paper we presents the HMM improved Naive Bayes method for Fraud Detection of Credit Card. Experimental results illustrate that both classifiers work differently for the same dataset. The purpose is to enhance the accuracy and enhance the flexibility of the algorithm.