In this paper, the authors proposes an empirical method of Anomaly detection by analyzing the spending habit of vendee. Proposed system models the sequence of operations in credit card transaction processing using a Hidden Markov Model (HMM) and shows how it can be used for the detection of frauds. 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. It is shown that credit card fraud can be detected using Hidden Markov Model during transactions.