Credit Card Fraud Detection Using HMM and DBSCAN

With the advent of cashless economy, the demand for credit cards has been rising steadily. With the increase in such transactions, fraud detection systems play a vital role. In this paper, we have modeled the operating phases in a credit card transaction processing. In the prototyped environment, the transaction detail of location is traced from the IP address. We have used two stages to detect the authenticity of a transaction HMM algorithm, a stochastic model for sequential data, that works on amount as the parameter, and DBSCAN that works on location of the transaction as the parameter. If the transaction doesnt pass through any of these phases, the card holder is alerted via an email. We have backed the efficiency of the approach by presenting an experimental analysis of the same.