Analysis of Pattern Identification Using Graph Database for Fraud Detection

Abstract

Internet is the main tool for e-business. E-transaction is made faster by Internet. With the increase of e-transaction internet fraud or e-business fraud is increasing. Credit fraud in the banking sector is a growing concern. Few sort of card (debit/credit) fraud is decreasing by providing detection and prevention system from banks and government. But card-not-present fraud losses are increasing at higher rate because of online transaction as there is no chance to use Chip and PIN as well as card is not used face-to-face. Card-not-present fraud losses are growing in an un-protective and un-detective way. This paper seeks to investigate the current debate regarding the fraud in the banking sector and vulnerabilities in online banking and to study some possible remedial actions to detect and prevent credit fraud. The research also reveals lots of channels of fraud in online banking which are increasing day by day. These kinds of fraud are the main barriers for the e-business in the banking sector. This paper devised a new approach for fraud detection in these sector with help of graph database & by matching pattern of previous frauds.