The Warning Research On Internet Financial Risk Based On The BP Neural Network

In recent years, e-commerce and network technology develop by leaps and bounds, the financial industries are also affected. Many smaller companies have huge capital demand, at the same time, the investment demand of the public is huge too, which promotes the development of the P2 P lending. Take P2 P as the example, it has great developmental potential from the combination of financial disintermediation and the Internet, not only broke through the previous constraints on geography and the space-time, but also makes it possible for everyone to communicate freely. In terms of P2 P mode, so many people have participated in it. But the flexible ways of raising and expending funds, unsound warning and regulatory policy lead to more and more financial fraud and Capital chain interruption。At the same time, in the case of our country’s Internet, as it is too late to carry out financial business,so that it is still in the initial stage, many aspects of the management is still not very comprehensive. With the development of the Internet, the new P2 P mode of Internet financial will face many difficulties and opportunities. We should study the corresponding risk warning model, make the seed of risk controlled as soon as possible, so as not to cause more serious damage. Warning analysis is not only helpful to the new type of model of P2 P, but also worth learning for the whole Internet financial which can have some demonstration effect.The research mainly studies the risk warning of P2 P network lending mode, respectively focuses on Internet finance, P2 P network lending and risk warning in order to gain influential risk elements of Internet financial development. Secondly, to set up relevant warning systems according to the risk types under the Internet financial P2 P mode from both aspects of indicators principles and risk forecast. Then combines the new KLR signal analysis and component analysis together and constructs the risk defense warning model. Thirdly, just takes P2 P network lending mode for example, this paper will choose 25 samples, to find out the risk information through network and relevant researchers’ studies, and then through analyzing, researching,concluding to have the final ranking position and total score. Fourthly, analysis from the P2 P credit risk review model based on the BP neural network, combined with some practical examples, to set out corresponding processing methods or opinions, so that the P2 P domain of Internet finance will move forward stably and operate smoothly.