![]() However, Chinese internet-based financial institutions have accumulated substantial financial risks due to the prosperity of the P2P lending industry. ![]() As of June 2018, the volume of the P2P net loan industry was 175 billion and 723 million RMB, and the Chinese P2P lending market became the largest worldwide. Five years later, 50 platforms were in operation, and the number jumped to 1931 as of December 2017, according to the statistics of (a web loan information platform). The earliest P2P company in China was created in 2006 1. As a developing country, China has experienced a major boom in P2P lending over the past five years at the same time, China is the leading market concerning both the total volume of loans and the number of borrowers. Zopa, the first P2P company, was set up in London in 2005 and was followed by high-speed growth of P2P lending companies worldwide. Peer-to-peer (P2P) lending is an online financial platform designed to provide small and microloans among strangers. Our methodology and findings will help regulators, banks and creditors combat current financial disasters caused by the coronavirus disease 2019 (COVID-19) pandemic by addressing various financial risks and translating credit scoring improvements.įinancial enterprises operating on the internet are developing rapidly with the advent of the Web 3.0 era. Our findings demonstrate important techniques for borrower screening by P2P companies and risk regulation by regulatory agencies. The accuracy and kappa value of the four methods all exceed 90%, and RF is superior to the other classification models. The results showed that borrowers who have passed video, mobile phone, job, residence or education level verification are more likely to default on loan repayment, whereas those who have passed identity and asset certification are less likely to default on loans. In our study, we applied four machine learning methods (random forest (RF), extreme gradient boosting tree (XGBT), gradient boosting model (GBM), and neural network (NN)) to predict important factors affecting repayment by utilizing data from in China from Thursday, January 1, 2015, to Tuesday, June 30, 2015. The latest literature reveals that existing risk evaluation systems may ignore important signals and risk factors affecting P2P repayment. Repayment failures of borrowers have greatly affected the sustainable development of the peer-to-peer (P2P) lending industry.
0 Comments
Leave a Reply. |