Abstract
Peer-to-peer (P2P) network lending is a new mode of internet finance that still holds credit risk as its main risk. According to the internal rating method of the New Basel Accord, in addition to the probability of default, loss given default is also one of the important indicators of evaluation credit risks. Proceeding from the perspective of loss given default (LGD), this paper conducts an empirical study on the probability distribution of LGDs of P2P as well as its influencing factors with the transaction data of Lending Club. The results show that: (1) the LGDs of P2P loans presents an obvious unimodal distribution, the peak value is relatively high and tends to concentrate with the decrease of the borrower’s credit rating, indicating that the distribution of LGDs of P2P lending is similar to that of unsecured bonds; (2) The total asset of the borrower has no significant impact on LGD, the credit rating and the debt-to-income ratio exert a significant negative impact, while the term and amount of the loan produce a relatively strong positive impact. Therefore, when evaluating the borrower’s repayment ability, it is required to pay more attention to its assets structure rather than the size of its total assets. When carrying out risk control for the P2P platform, it is necessary to give priority to the control of default rate.
Highlights
Since 2011, with the rapid development of internet finance in China, peer-to-peer (P2P) network lending has sprung up suddenly, giving rise to Alibaba, Suning Micro-finance, and a large number of P2P lending platforms
According to the internal rating theory introduced by the New Basel Capital Accord, the analysis of credit risk valuation can be carried out from two aspects: namely, the default rate reflecting the possibility of default and loss given default (LGD) reflecting the severity of the loss after default
Through the empirical analysis of default loans of the Lending Club, this paper describes probability distribution characteristics and influencing factors of LGDs in P2P network lending
Summary
Since 2011, with the rapid development of internet finance in China, peer-to-peer (P2P) network lending has sprung up suddenly, giving rise to Alibaba, Suning Micro-finance, and a large number of P2P lending platforms. Due to the imperfect financial system, China is facing a more serious phenomenon of credit rationing, there is a strong demand for financing and lending in society, and traditional commercial banks find it hard to meet this demand Under this historical background, China’s P2P platforms have ushered in an explosive growth. Different from the existing research, this paper has made some progress in the following two aspects: first of all, this paper deeply analyzes the influencing factors of P2P network credit from the perspective of loss given default (LGD) It selects the transaction data of Lending Club to depict the probability distribution characteristics and influencing factors of LGDs in P2P network lending. The research of this paper mainly includes the following parts: the second part is the literature review, the third part presents the theory analysis and research hypothesis, the fourth part displays the empirical analysis, and the fifth part includes the conclusions and suggestions
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