Research on Personal Credit Risk Assessment Index System Based on Internet Social Big Data

Abstract

The traditional personal credit risk assessment index system is difficult to adapt to the needs of today's Internet era, and Internet social big data can easily and efficiently collect personal behavior data on the Internet and provide important information for discriminating personal credit. This paper discusses the advantages of Internet social big data and the scientific and rationality of introducing it into the personal credit risk assessment index system. It establishes 19 evaluation indicators, uses the AHP method to assign weights to each indicator, and quantifies the indicators. Finally, a personal credit risk assessment index system based on Internet social big data was formed. The TOPSIS method was used to analyze the simulation data and verify the rationality of the index system.