| Since the birth of Internet technology, because of it can maximum get rid of the limits of time and space, it makes the efficiency of information transfer greatly increased. And Internet technology gradually penetrate into people’s daily life, playing an increasingly important role. Because of this, various traditional industries are competing cross-integration with Internet, attempting to further develop them with the help of Internet. Traditional financial industry is also actively integration with Internet, then we have the Internet financial industry and rapidly development. The rise of Internet financial industry, to some extent, has caused a shock to traditional financial sector, and become a powerful force in modern financial industry now.As an important part of Internet finance, online P2P lending develop rapidly and become popularity in various nations, thus, turns into the focus of industry and academic world. Online P2P lending is the abbreviation of "Online Peer to Peer Lending", refers to a microfinance lending model between individuals via online platforms.China’s first online P2P lending platform established in 2007. Within ten years’explosive growth, China’s online P2P lending market has nearly 4000 platforms existed, the monthly trade volume close to 100 billion, involving over four million active investors and borrowers. From the market scale perspective, China’s online P2P lending market ranking the first place in the world.The appearance and development of online P2P lending encountered the promoting of interest rate liberalization and mass entrepreneurship and innovation endorsed by China central government. Internet finance, particularly online P2P lending offers a solution to the financing difficulty in SMEs and individual entrepreneurs. Further, in July 2015, the State Council of China issued "The State Council guiding opinions on promoting Internet Plus Action". Inclusive finance was be included in this "Internet Plus Action" as a key target, which means Internet finance become a key national strategy of China. Obviously, China values Internet finance including online P2P lending very seriously. But the present situation is not optimistic for the long term healthy development of online lending industry. On one hand, online lending scale expansion rapidly and the state attaches great importance to it, on another hand, the personal credit reference system construction is seriously lagging behind. Moreover, the whole society is filled with serious distrust, which credit and mutual trust is the basement for online lending platform healthy running. Moreover, regulatory rules have not yet implemented, the competent authorities is unclear. The outcome of this sadness situation is that, online P2P lending platforms outbreak crises and bankruptcy frequently. Naturally, leads the investors’enthusiasm be severe depressed, and jeopardized the whole online lending industry in its infant period. For national perspective, the strategy of inclusive finance may be damaged. Therefore, the study of Internet finance, online P2P lending platform risk pre-warning and risk prevention, whether it is for regulators, practitioners, investors, or scholars all have a significant practical significance.This dissertation starts by reviewing online P2P lending literatures and third-party reports, for better understanding of the development status of domestic online P2P lending platform. Classify and compare the business model of online P2P lending industry, then find out risk related factors both micro and macro level. Analysis these factors separately, in order to find risk indicators to establish online P2P lending risk pre-warning model. Subsequently, we collect 23 different risk metrics indicators of 18 sample platforms by randomly chosen, through third-party website, by the principle of comprehensive, sensitive, operability and continuity. Then we build a three-layer model, with one objective level, four secondary index levels and 23 third indicators. After that, we standardized all indicators through maximum-minimum standardization method, filtered 17 indicators out by correlation and principle component analysis, weighted different levels by entropy weight and adjusted expert evaluation weight method. After added in macroeconomic index as a macroeconomic effect adjust, finally we have a risk score ranking result for all sample platforms. By passing Spearman rank correlation test with different third-party ranking, we believe the result of our risk pre-warning model is scientific and doable. Finally, we try to use adjusted KLR signal lights model to divide sample platform and display them out into five different risk levels.In general, this quantitative risk pre-warning online P2P lending platform model is both simple and feasible in this status quo. We wish this study can provide a helpful reference for all participants in Internet finance, particular in online P2P lending sector.The main contents of this dissertation organized as follows:Chapter one, introduction. Introduce the background, meaning and purpose of this dissertation.Chapter two, the development status of online P2P lending platforms. This chapter is divided into two parts. In the first half, introduces the current situation of online P2P lending platform development, classified the operating business model, and compared them, through third-party industry report. The second half focuses on analysis the risk factors which impact on online P2P lending platforms. In this dissertation, we classified factors into two categories, namely, macro and micro. Then elaborate on these factors.Chapter three, establishment of online P2P lending platform risk pre-warning model. This chapter is also divided into two parts, the first part elaborate with which standards to select risk warning indicators to ensure comprehensiveness, sensitivity, operability and continuity. The second part describes the mathematical and econometric analysis method or treatment in empirical study.Chapter four, empirical study. According to the standards and treatment method of chapter three. In this empirical study, we select 18 sample online P2P platforms,4 fist level indicators and 23 secondary level indicators to build this risk pre-warning model. After a procedure of standardization, indicator filtration, index empowerment, risk score ranking, rank correlation verification and signal lights display. The final ranking result having a high positive correlation with other third-party ranking, this proves this quantitative risk pre-warning model has certain scientificness and practicability.Chapter five, conclusion and outlook. In this chapter, we take typical platforms form each risk display zone out conduct brief review. Afterwards, conduct a dissertation summarize, including the weaknesses and the research direction of further study in the future. |
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