Internet Financial Risk Control System based on Artificial Intelligence

The operational model of businesses has changed from the old model to e-commerce due to the acceleration of global economic integration, the quick development of information technology, the Internet craze, and the explosive growth of the Internet economy. Internet finance is becoming more and more of a focus for businesses and is a significant component of e-commerce. Internet finance is an important part of e-commerce and has attracted the attention of more and more enterprises. The development of network technology has pushed the originally closed local area network financial information system into the open Internet world. Network financial information systems bring benefits to enterprises, but they also bring risks to enterprises. Effective risk control needs to be implemented on the basis of analyzing the risks. Based on the above issues, this article discusses how to build an online financial risk control system through artificial intelligence algorithms. This article constructs an online financial risk prediction model based on the BPNN (Back propagation neural network) algorithm, conducts algorithm training and testing through historical data sets, and finally conducts comparative analysis with the logistic regression model algorithm. The results show that the probability of misjudging financial crisis as financial normality in the logistic regression model is 18.97 %, which is higher than the algorithm model in this article.