In recent years, numerous Chinese peer-to-peer (P2P) lending platforms have collapsed, prompting us to investigate the regulation and monitoring of the fintech industry. Using a unique dataset of P2P lending platforms in China, we examine the effect of government monitoring on platform collapses. Exploiting platforms’ locational proximity to regulatory offices as a proxy for government monitoring, we show that greater geographical distance results in a higher likelihood of platform collapse. Specifically, for every 10% increase in the driving distance from the platform to the local regulatory office, the likelihood of collapse increases by 10.2%. To establish causality, we conduct a differencein-differencesanalysis that exploits two exogenous shocks: government office relocation and subway station openings. We further explore two underlying channels: the information channel through which greater regulatory distance reduces the likelihood of regulators’ onsite visits and the resource constraint channel, through which greater regulatory distance significantly increases the local regulatory office’s monitoring costs. Overall, this study highlights the importance of onsite regulatory monitoring to ensure the viability of online lending platforms.

In recent years, numerous Chinese peer-to-peer (P2P) lending platforms have collapsed, prompting us to investigate the regulation and monitoring of the fintech industry. Using a unique dataset of P2P lending platforms in China, we investigate the effect of the information environment on regulatory monitoring and platform collapse. Using the platforms’ proximity to regulatory offices as a proxy for information asymmetry, we show that an increase in distance reduces regulatory monitoring and increases the likelihood of platform collapse. Specifically, for every 1% increase in the driving distance between the local regulatory office and a P2P lending platform’s office, the platform’s likelihood of collapse increases by 1.011%. To establish causality, we conduct a difference-in-differences analysis that exploits two exogenous shocks: government office relocation and subway station openings. We provide evidence that proximity enhances monitoring quality by facilitating soft information collection, reducing platform failures. We further find two channels of this effect: (1) the information channel through which greater regulatory distance reduces the likelihood and frequency of regulators’ on-site visits and (2) the resource-constraint channel, through which greater regulatory distance significantly increases the local regulatory office’s monitoring costs. Overall, this study highlights the importance of the acquisition of soft information for regulatory monitoring to ensure the viability of fintech firms.

我们发现，股市泡沫和信贷市场中的信用风险存在因果关系。我们分析了来自人人贷（国内头部P2P众筹平台）的超过45万笔贷款数据，时间为2015年，当时A股正经历非理性的大起大落。随着上证综指突破3500点，散户们积极进入股市，并通过P2P平台融资，我们发现，此时P2P平台贷款的违约率以及违约程度都有了大幅提高。对于低质量贷款以及过分自信的贷款者，这种效应更加显著。其他一系列P2P市场状态指标，也都出现恶化。总之，我们认为，金融科技的发展会扩大金融风险，促使风险在不同市场之间蔓延。

Investors have limited attention, especially when getting busy. They also possess a capability of fast thinking that requires little, if any, attention, although fast thinking leads to biased judgement and inferior outcome. From a Chinese online peer-to-peer lending market, we document a substantial amount of instant loan bids (i.e., those confirmed within only a few seconds) which help identify fast thinking. We find that lending decisions made within busy working hours with more attention constraint have significantly higher likelihood of being instant and significantly lower investment performance, suggesting that investors are prone to fast thinking when their attention becomes limited.

Peer-to-Peer lending platforms encourage borrowers to obtain various credit certificates for information disclosure. Using unique data from one of China's largest Peer-to-Peer platforms, we show that borrowers of lower credit quality obtain more certificates to boost their credit profiles, while higher-quality ones do not. Uninformed credulous lenders take these nearly costless certificates as a positive signal to guide their nvestments. Consequently, loans applied by borrowers with more credit certificates have higher funding success but worse repayment performance. Overall, we document credit certificates fail to accurately signal borrowers' qualities due to adverse selection, resulting in distorted credit allocation and investment inefficiency.

In this paper we use the data from “paipaidai”, an online peer-to-peer lending platform in China, to testify whether mood affects the efficiency of credit approval by individual. Refering to the studies in Psychology and Financial Economics, we employ season, temperature and weather as mood proxies, and crotrol the variables related to the quality of loan to study the credit approval behavior under different mood condition. The results suggest that the efficiency of credit approval is significantly correlated with mood—positive mood would improve the efficiency, while negative mood would reduce it. Specifically, loan examined under better mood condition (e.g. spring, comfortable temperature, and sunny days) has significantly higher probability of approval, but lower probability to default if approved; and that examined under lower mood condition shows lower probability of approval and higher probability to default if approved. This effect of mood is even stronger when a loan application to judge is more complex, atypical, or unusual. Moreover, investor sentiment, denoted by closed-end fund premiums, has the same effect on credit approval as well.