| At present,the development of China’s new financial industry has achieved a remarkable leading position in the world.Business models such as online consumer finance,online lending platform(P2P),online insurance,online monetary funds and mobile payment have all achieved remarkable results.Among them,the online lending platform industry,as an important part of our country’s new financial format,provides an effective solution to the financing of small and micro enterprises and personal lending problems.On the one hand,the development of China’s new financial industry is of great significance to promote China to achieve high-quality economic growth,and financial innovation has also brought new vitality to the financial system.However,on the other hand,due to the lack of risk awareness among Chinese people,the relative lack of financial knowledge and the lag of supervision and other reasons,in recent years,China’s new financial forms have brought new risks and hidden dangers while providing convenience.Taking the online loan platform industry as an example,as a typical representative of financial innovation,the industry was born beyond the scope of China’s financial supervision,so that it was in a period of fuzzy supervision.Due to the low entry barrier of the industry,a large number of non-financial workers rushed into the market,and thousands of online lending platforms grew wild.The unsound and lag of the platform risk supervision aggravated the disorderly development of the whole industry,and finally the risks broke out.In a general sense,financial innovation is always accompanied by the continuous deepening of people’s understanding of innovation,and gradually identify,control and eliminate risks,which is the general law of financial development.Once the related risks of new financial forms cannot be properly resolved,it may increase the difficulty of preventing systemic financial risks in China.Therefore,it is of great significance to study the risks and prevention and control of new financial forms in China.By sorting out the development of our country’s online lending industry,we find that the risks in the online lending platform industry are more special and complex than other types of online lending industry.Online lending platform industry is a new type of business that affects many individual lenders and borrowers.The model,the internal driving force of its rapid development and the challenges it faces are also more representative in the online lending industry.Therefore,we focus on the online lending platform industry,and conduct an empirical study on its risk identification and risk transmission.In addition,we analyze the relationship between online public opinion and our country’s new financial formats,investor sentiment and online lending platform industry risks.After the relationship between the investor sentiment and online lending platform industry risks is analyzed,we based on its investor sentiment,a prediction model for risk early warning indicators of our country’s online lending platform industry is constructed.The research results show that,first,among the three types of online lending industry in our country,the risks of online consumer credit and digital bank loans are relatively controllable.However,the risks in the online lending platforms are more complicated,mainly including credit risk,liquidity risk,operational risk,legal risk,and market risk.Secondly,in order to better judge the risks of online lending platform industry,we comprehensively use the platform itself,online public opinion and the evaluation information of the third-party information websites to construct a qualitative and quantitative combination of online lending platform risk evaluation system.And further analyze the difference between the indicators data of the sample online lending problem platform and the normal platform.In the empirical part of risk identification,according to the "no free lunch" theorem in machine learning theory,we test the several empirical performance of machine learning and deep learning algorithms on the risk research problem of China’s online lending platform industry.Among them,there are a total of 4 models with an accuracy rate of 80%and above,and the SVM model has the highest accuracy rate,and for the more noteworthy results of the problem platform evaluation,the SVM model also has the best problem platform accuracy results.Then,based on the e-zubao risk event in the online lending platform industry,we construct a model from two perspectives:the regional situation of the platform and the recovery time of the platform after the risk event,and carries out an empirical analysis on the impact of risk transmission in China’s online lending platform industry.The research finds that:at the regional level,the platforms in the region with stronger financial and economic development,or the online lending platform industry with more vigorous development,are more likely to generate risks during the risk transmission period.However,in terms of recovery time,platforms with larger scale and lower per capita investment need less recovery time for the transaction level to recover.Next,based on the key analysis of the top ten indicators variables in the importance of identifying the risk situation of online lending platforms,we believe that in our country’s online lending platform industry,the product transaction data of both lenders and borrowers can most directly reflect the development of the industry,and provide investors with a good indication.Among them,the average lending interest rate of online lending platform market products and the average lending term of transactions are the two most noteworthy indicators,which can be used as risk early warning indicators for our country’s online lending platform industry and deserve further analysis.In addition,after practical demonstration,we find that the network public opinion information is related to the dynamics of the new financial business field,and the emotional expression excavated from the network public opinion is conducive to predicting the dynamic indicators changes of the financial technology stock market.Therefore,we further excavate the investor sentiment of the online lending platform industry,and build a bridge between the investor sentiment of the online lending platform participants and the risk warning indicator data of the online lending platform market to construct a prediction model.The empirical results show that,compared with the basic model,the prediction model constructed in this paper shows better prediction ability in the online lending platform market with fast data update,which provides a certain data support for measuring the product transaction status of the online lending platform market.Finally,according to the conclusions of our research,we put forward relevant policy suggestions for the future development,product design and risk prevention and control of our country’s online lending industry. |
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