Risk control of online P2P lending in China based on health investment

Due to the imperfection of Chinese current medical security system, a large proportion of residents’ income is spent on maintaining their health. For the sudden and expensive nature of these costs, more and more people choose to borrow money from online P2P leading. While providing investors with health investment opportunities, Chinese online P2P lending market is controversial due to its risks. In this paper, the personal credit evaluation model is established based on support vector machine (SVM), and the genetic algorithm (GA) is introduced to optimize the parameters of the model. The results show that the risks in Chinese online P2P lending market are controllable. The healthy development of online P2P leading industry is conducive to improving the quality of life of Chinese people.