Internet Financial Risk Model Evaluation and Control Decision Based on Big Data

Abstract

Internet finance is the application of advanced information technology to traditional finance. Internet finance is accelerating its growth, and its performance is most obvious in the financial market. The Internet financial reduces costs of traditional financial, which makes it more civilian. The unstable factors of Internet finance, such as regulation, credit reporting, and network security, lead to a gradual increase in risks. The current Internet financial risk model is slow to deal with risks and cannot solve the financial risks that arise in time to ensure the safety of the platform. In order to solve this problem, the big data technology was applied to the Internet financial risk model to evaluate and control financial risks. The default rate, rate of return, risk control time, model performance score, and other aspects of the Internet financial risk model using big data were tested. It is found that by applying big data technology to the Internet financial risk model, the customer default rate decreased by 6.14%, the yield increased by 7.6%, the time to deal with risks was reduced by 0.46 minutes, and the model performance score was improved by 0.796 points. Big data technology can effectively control and avoid Internet financial risks and help investors avoid risks.