Real-time credit card fraud detection using Streaming Analytics

Abstract

With the growing popularity of the internet, everything is available at our doorstep and convenience. The rapid increase in e-commerce applications has resulted in the increased usage of the credit card for offline and online payments. Though there are various benefits of using credit cards such as convenience, instant cash, but when it comes to security credit card holders, banks, and the merchants are affected when the card is being stolen, lost or misused without the knowledge of the cardholder (Fraud activity). Streaming analytics is a time-based processing of data and it is used to enable near real-time decision making by inspecting, correlating and analyzing the data even as it is streaming into applications and database from myriad different sources. We are making use of streaming analytics to detect and prevent the credit card fraud. Rather than singling out specific transactions, our solution analyses the historical transaction data to model a system that can detect fraudulent patterns. This model is then used to analyze transactions in real-time.