P2P Lending Platforms Research Articles

Breaking New Ground: The Americas Alternative Finance Benchmarking Report

Breaking New Ground: The Americas Alternative Finance Benchmarking Report

Who Can Get Money? Evidence from the Chinese Peer-To-Peer Lending Platform

This paper explores how borrowers’ financial and personal information, loan characteristics and lending models affect peer-to-peer loan funding outcomes. Using a large sample of listings from one of the largest Chinese online P2P lending platforms, we find that those borrowers earning a higher income or owning a car are more likely to receive a loan, pay lower interest rates and are less likely to default. The credit grade assigned by the lending platform may not represent the creditworthiness of potential borrowers. we also find that the offline process in the P2P online lending platform exerts significant influence on the lending decision.

P2P Lending Risk Contagion Analysis Based on a Complex Network Model

This paper analyzes two major channels of P2P lending risk contagion in China—direct risk contagion between platforms and indirect risk contagion with other financial organizations as the contagion medium. Based on this analysis, the current study constructs a complex network model of P2P lending risk contagion in China and performs dynamics analogue simulations in order to analyze general characteristics of direct risk contagion among China’s online P2P lending platforms. The assumed conditions are that other financial organizations act as the contagion medium, with variations in the risk contagion characteristics set under the condition of significant information asymmetry in Internet lending. It is indicated that, compared to direct risk contagion among platforms, both financial organizations acting as the contagion medium and information asymmetry magnify the effect of risk contagion. It is also found that the superposition of media effects and information asymmetry is more likely to magnify the risk contagion effect.

How Can New Online P2P Lending Platform Catch up from Behind—Take Ebaodai as an Example

Internet finance has become extremely popular since 2013, especially online P2P lending, which appears like mushrooms. And at the same time, the number of problematic platform is rising. Many platforms appeared to be difficult to withdraw deposit; some had even closed. For the lack of supervision and credit system in our country, this article takes the up-rising star Ebaodai as the research object to analyze its business model and characteristic of platform running. Then the article explored and analyzed how new P2P lending platform to stand out among numerous newly increased ones from a platform standpoint.

Market Mechanisms in Online Peer-to-Peer Lending

Online peer-to-peer lending (P2P lending) has emerged as an appealing new channel of financing in recent years. A fundamental but largely unanswered question in this nascent industry is the choice of market mechanisms, i.e., how the supply and demand of funds are matched, and the terms (price) at which transactions will occur. Two of the most popular mechanisms are auctions (where the “crowd” determines the price of the transaction through an auction process) and posted prices (where the platform determines the price). While P2P lending platforms typically use one or the other, there is little systematic research on the implications of such choices for market participants, transaction outcomes, and social welfare. We address this question both theoretically and empirically. We first develop a game-theoretic model that yields empirically testable hypotheses, taking into account the incentive of the platform. We then test these hypotheses by exploiting a regime change from auctions to posted prices on one of the largest P2P lending platforms. Consistent with our hypotheses, we find that under platform-mandated posted prices, loans are funded with higher probability, but the preset interest rates are higher than borrowers’ starting interest rates and contract interest rates in auctions. More important, all else equal, loans funded under posted prices are more likely to default, thereby undermining lenders’ returns on investment and their surplus. Although platform-mandated posted prices may be faster in originating loans, auctions that rely on the crowd to discover prices are not necessarily inferior in terms of overall social welfare. This paper was accepted by Chris Forman, information systems.

An Effective Interval-Valued Intuitionistic Fuzzy Entropy to Evaluate Entrepreneurship Orientation of Online P2P Lending Platforms

This paper describes an approach to measure the entrepreneurship orientation of online P2P lending platforms. The limitations of existing methods for calculating entropy of interval-valued intuitionistic fuzzy sets (IVIFSs) are significantly improved by a new entropy measure of IVIFS considered in this paper, and then the essential properties of the proposed entropy are introduced. Moreover, an evaluation procedure is proposed to measure entrepreneurship orientation of online P2P lending platforms. Finally, a case is used to demonstrate the effectiveness of this method.

Herding behavior in online P2P lending: An empirical investigation

We study lender behavior in the peer-to-peer (P2P) lending market, where individuals bid on unsecured microloans requested by other individual borrowers. Online P2P exchanges are growing, but lenders in this market are not professional investors. In addition, lenders have to take big risks because loans in P2P lending are granted without collateral. While the P2P lending market shares some characteristics of online markets with respect to herding behavior, it also has characteristics that may discourage it. This study empirically investigates herding behavior in the P2P lending market where seemingly conflicting conditions and features of herding are present. Using a large sample of daily data from one of the largest P2P lending platforms in Korea, we find strong evidence of herding and its diminishing marginal effect as bidding advances. We employ a multinomial logit market-share model in which relevant variables from prior studies on P2P lending are assessed.

Mitigating Adverse Selection in P2P Lending – Empirical Evidence from Prosper.com

This paper presents novel empirical evidence on the success of efforts by P2P lending platforms to limit adverse selection using a unique sample of 5,385 credit transactions on the internet platform Prosper.com. The results of our regressions on the probability of a credit bid’s successful funding show that all variables for which a significant influence on the probability of funding success could be found describe information which is verified by Prosper.com. Conversely, all non-verified variables do not possess any significant influence on the dependent variable thus confirming our hypothesis that the screening of potential borrowers is a major instrument in mitigating adverse selection in P2P lending and preventing the online market to collapse. Moreover, we find evidence confirming the proposition that the screening of potential borrowers by groups can help mitigate adverse selection. Group membership, however, does also seem to have a positive influence on the probability of a credit bid expiring, a novel finding of this study.

Emergence of Financial Intermediaries in Electronic Markets: The Case of Online P2P Lending

AbstractWe analyze the role of intermediaries in electronic markets using detailed data of more than 14,000 originated loans on an electronic P2P (peer-to-peer) lending platform. In such an electronic credit market, lenders bid to supply a private loan. Screening of potential borrowers and the monitoring of loan repayment can be delegated to designated group leaders. We find that these market participants act as financial intermediaries and significantly improve borrowers’ credit conditions by reducing information asymmetries, predominantly for borrowers with less attractive risk characteristics. Our findings may be surprising given the replacement of a bank by an electronic marketplace.

P24 Factors in successful patient recruitment applying the six-box organizational model in a large VA cooperative study

This study reviews the literature of online peer-to-peer (P2P) lending from 2008 until 2020 as an emergent but fast spreading phenomenon in the context of digital finance. Previous literature is geographically skewed towards United States and China with focus on determinants of funding success and loan attributes. Recent studies shift from using logit and survival analysis methods to examine funding success and default predictions, towards applying artificial intelligence. There is a controversial debate regarding adopting a self-regulatory approach versus stricter financial institutions-based regulations with a few studies suggesting a hybrid approach. We suggest several avenues for future research, such as examining the determinants and performance of P2P lending platforms in emerging and developing markets; regulatory differences, the effects of behavioral characteristics such as cultural impact, language, information technology literacy, and the innovation quotient on P2P funding attributes; and the relationship between P2P lending and traditional finance channels.