A Monitoring Model of Unusual Transactions Based on Complex Event Processing

Abstract

Faced with the demand for real-time "big data" processing, the existing financial risk early warning systems are generally difficult to identify hidden risks in massive data information quickly and accurately. This paper introduces a complex event processing technology (CEP), proposes a method of real-time monitoring for "big data", establishes a monitoring model of unusual transactions, designs and realizes a system based on this model. The model contains data acquisition and encapsulation module, custom rules modeling module and results display module. Using real data of a security company to test the system, the results show that, it can identify hidden risks in unusual transactions accurately, and the speed of processing is improved significantly comparing with the system which is based on traditional database analysis method.