Internet financial risk prevention is an important area for financial risk prevention. In recent years, a series of vicious high-risk events, such as cash lending and P2P platform running, have caused a great negative impact on the reputation of the Internet financial industry, which has aroused great concern from all walks of life. Based on big data analysis technology, this paper constructs an improved algorithm model, and carries out high-precision risk warning for China's Internet financial risk. The forecast data is basically consistent with the actual situation, and the prediction accuracy reaches 90%. It can be seen that the improved model based on the decision tree algorithm has higher prediction accuracy for Internet financial risk warning. This paper systematically sorts out the risks of China's Internet finance from two dimensions: risk type and main risk. And pointed out that the current Internet finance industry in China has a large overall compliance risk, and insufficient infrastructure construction leads to fraud risks. Separate industry supervision has a regulatory vacuum, arbitrage risks are more obvious, and China's financial consumer quality is not high, Internet financial institutions Improper exemption is risky. On this basis, it is proposed to speed up the construction of a multi-integrated Internet financial risk prevention system including the internal risk control system, the industry association self-discipline system, the government administrative supervision system and the effective social supervision system.
Application of Association Rules Big Data Analysis in Building Safety Production Supervision System
