Summary:
China's P2P (peer-to-peer) online lending industry has experienced numerous twists and turns in its development process, during which there have been several serious platform crises that have hindered the healthy development of the industry. Default risk has become an unavoidable problem, resulting in the loss of capital allocation efficiency in the industry. Previous studies have focused on active defaults, in which borrowers intentionally or strategically default despite having the ability to repay; passive defaults have been discussed less frequently. On many P2P platforms, borrowers can independently set borrowing rates in advance and make loan orders. Due to their relatively weak bargaining skills, borrowers are likely to produce pricing deviation, causing an unexpected rise of repayment pressure. When the pressure exceeds the borrower's ability, the borrower will have to default. This paper argues that even if there is no active default intention, excessive pricing deviation will often break the borrower's income balance and lead to passive default. We further propose that the borrower, as the party with more information, will try to reduce pricing deviation through information whitewashing and reverse his/her inferior position to obtain a larger bargaining surplus. We therefore study the characteristics of this behavior and investors' reaction to it. In the theoretical part, based on behavior asset pricing theory and the pricing mechanism of Renrendai.com, this paper explores the reasons for pricing deviation. In an attempt to obtain a lower borrowing rate, borrowers may use unverifiable soft information; consequently, this paper discusses information whitewashing. Considering reputation cost and income balance, this paper also analyzes the relationship between pricing deviation and default risk. In the empirical part, with data from Renrendai.com from 2014 to 2018, this paper studies the factors influencing the pricing deviation of peer-to-peer borrowers and the relationship between pricing deviation and passive default risk. Pricing deviation is obtained through a stochastic frontier approach by dividing interest rate into an efficient part and an inefficient part. The paper finds substantial pricing deviation among borrowers, which varies between different groups. Borrowers' whitewashing fails to reduce pricing bias and may even backfire. Furthermore, when the borrower's reputation cost is higher than the lending rate, defaults are mainly passive. Even if the borrower does not actively intend to default, the greater the pricing deviation, the tighter the borrower's remaining income, and the greater the likelihood that the number of overdue payments and the proportion of debt owed will increase, which leads to greater risk of passive default. Based on these empirical results, this paper makes several suggestions. First, the rate pricing mechanism should be improved, which means that rate flexibility should be increased and P2P interest rate marketization should be promoted. Second, information disclosure should be strengthened and information standardization should be implemented. Finally, it is necessary to improve default risk control, understand borrowers' motivations, reduce the probability of passive default, and improve the efficiency of capital allocation. Our study contributes to the literature in the following ways. First, the cost stochastic frontier (SFA) is used to construct the pricing deviation index. In contrast to the literature, this construction method comprehensively considers loan availability and the post-loan default risk of a loan order, which classifies the optimal interest rate and pricing deviation more objectively and reasonably. Second, focusing on the limits of platform information verification, this paper investigates the information whitewashing behavior of borrowers and the reaction of investors, and it reveals the information transmission and bargaining mechanism of both parties on the platform. Third, it outlines the reasons for borrowers' passive default, examines the relationship between pricing deviation and passive default, and enriches the risk control strategy of P2P platforms.
封思贤, 那晋领. P2P借款人的定价偏差与被动违约风险——基于“人人贷”数据的分析[J]. 金融研究, 2020, 477(3): 134-151.
FENG Sixian, NA Jinling. Pricing Deviation and Passive Default Risk of Peer-to-Peer Borrowers: An Analysis Based on Transaction Data from Renrendai.com. Journal of Financial Research, 2020, 477(3): 134-151.
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