Herding behaviour in P2P lending markets (original) (raw)
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Dynamics of bidding in a P2P lending service: effects of herding and predicting loan success
2011
Abstract Online peer-to-peer (P2P) lending services are a new type of social platform that enables individuals borrow and lend money directly from one to another. In this paper, we study the dynamics of bidding behavior in a P2P loan auction website, Prosper. com. We investigate the change of various attributes of loan requesting listings over time, such as the interest rate and the number of bids.
Journal of Management Information Systems (JMIS) , 2023
This paper analyzes the herding behavior that characterizes lenders’ lending decisions on a microloan platform and explains how rational herding behavior can resolve the information-asymmetry problem, which is a well-known reason for the failure of online microloan platforms. Using a set of panel data on individual lending decisions acquired from Paipaidai.com (PPDai), an online microloan platform, we examine the influence of the lending decisions of prominent, experienced lenders on novice lenders to identify rational herding behavior. Our empirical analysis demonstrates that rational herding behavior can in fact efficiently reduce lender loss from borrower defaults caused by limited information. Although it is typically assumed that herding behavior is irrational, we find that it can be rational in this context and can thus shed light on why PPDai has succeeded while most other microloan platforms have failed. Accordingly, we make three key contributions: (1) we use heterogeneous herding effects to empirically determine whether lenders’ herding behavior on PPDai is rational based on observational learning; (2) we investigate the moderating effect of borrower credit and novice-lender experience on herding, and we leverage this heterogeneity in lender experience to better explain loan results; and (3) because PPDai publicly provides potential lenders with a transparent credit score—in contrast to platforms like Prosper.com, which leverage hidden proprietary credit information from Experian—we further analyze the credit composition of prominent lenders to better understand the crucial determinants of rational herding. In fact, our follow-up survival simulations indicate that without rational herding, the total number of successful PPDai loans would have decreased by around 46% during the study period—a finding that further underlines the crucial influence of rational herding and the unique contextual factors of PPDai that have fostered it.
Friendships in Online Peer-to-Peer Lending: Pipes, Prisms, and Social Herding
SSRN Electronic Journal, 2000
This paper investigates how friendship relationships act as pipes, prisms, and herding signals in a large online Peer-to-Peer (P2P) lending site. By analyzing decisions of lenders, we find that friends of the borrower, especially close offline friends, act as financial "pipes" by lending money to the borrower. On the other hand, the "prism" effect of friends' endorsements via bidding on a loan negatively affects subsequent bids by third parties. However, when offline friends of a potential lender, especially close friends, place a bid, a "relational herding" effect occurs as potential lenders are likely to follow their offline friends with a bid.
Peer-to-peer lending and bias in crowd decision-making
PLOS ONE
Peer-to-peer lending is hypothesized to help equalize economic opportunities for the world's poor. We empirically investigate the "flat-world" hypothesis, the idea that globalization eventually leads to economic equality, using crowdfinancing data for over 660,000 loans in 220 nations and territories made between 2005 and 2013. Contrary to the flat-world hypothesis, we find that peer-to-peer lending networks are moving away from flatness. Furthermore, decreasing flatness is strongly associated with multiple variables: relatively stable patterns in the difference in the per capita GDP between borrowing and lending nations, ongoing migration flows from borrowing to lending nations worldwide, and the existence of a tie as a historic colonial. Our regression analysis also indicates a spatial preference in lending for geographically proximal borrowers. To estimate the robustness for these patterns for future changes, we construct a network of borrower and lending nations based on the observed data. Then, to perturb the network, we stochastically simulate policy and event shocks (e.g., erecting walls) or regulatory shocks (e.g., Brexit). The simulations project a drift towards rather than away from flatness. However, levels of flatness persist only for randomly distributed shocks. By contrast, loss of the top borrowing nations produces more flatness, not less, indicating how the welfare of the overall system is tied to a few distinctive and critical country-pair relationships.
ICSSSM11, 2011
In online P2P lending market, borrowers need to make strategic decisions, which will determine they will get the loans or not. In this study, we firstly investigate what and how the decisions made by borrowers influence the auction results. The empirical results display that borrower' decisions, e.g., loan amount, interest rate will determine whether she could successfully fund loan or not, especially loan amount requested by borrowers. Then, it is focus on analyzing the difference of two borrower's critical decisions (loan amount and interest rate) among successful, unsuccessful capable and incapable listings, and find out that borrowers of three types of listings make heterogeneous decisions. Finally, we provide some suggestions to online P2P lending market about borrowers' decisions aid services based on the results, which could be a contribution with the practical implementation of borrower decision support system.
Networking with Peers: Evidence from a P2P Lending Platform
2020
The paper investigates the role of network centrality in predicting borrowers’ and lenders’ behavior in peer-to-peer (P2P) lending. The empirical analysis of data from Renrendai, a leading lending platform in the People’s Republic of China, reveals that the lenders who are at the center of a network not only invest larger amounts but also invest more swiftly than their peers, reflecting the information advantage arising from their position in the network. Furthermore, the borrowers who are at the center of a network are able to borrow at lower interest rates and with higher success rates. At the same time, they are less likely to default. These findings imply that, in the P2P lending market, network linkages not only enhance market efficiency but also encourage reputation protection.
Lending Behavior and Community Structure in an Online Peer-to-Peer Economic Network
2009 International Conference on Computational Science and Engineering, 2009
Increasingly, economic transactions are taking place over social networks. We study the static and dynamic characteristics of a peer-to-peer lending network through 350,000 loan listings and accompanying member profiles from the online marketplace Prosper.com. Our results imply that social factors such as participation in affinity groups and descriptive profile text are correlated with financial indicators; at the same time, we see evidence of suboptimal lending decisions, minimal learning, and herding behavior in the network. We discuss implications and suggest possible improvements to the online peer-to-peer lending model.
P2P Lending: Information Externalities, Social Networks and Loans' Substitution
Banking & Insurance eJournal, 2017
Despite the lack of delegated monitor and of collateral guarantees P2P lending platforms exhibit relatively low loan and delinquency rates. The adverse selection is indeed mitigated by a new screening technology (information processing through machine learning) that provides costless public signals. Using data from Prosper and Lending Club we show that loans' spreads, proxing asymmetric information, decline with credit scores or hard information indicators and with indications from "group ties" (soft information from social networks). Also an increase in the risk of bank run in the traditional banking sector increases participation in the P2P markets and reduces their rates (substitution effect). We rationalize this evidence with a dynamic general equilibrium model where lenders and borrowers choose between traditional bank services (subject to the risk of bank runs and early liquidation) and P2P markets (which clear at a pooling price due to asymmetric information, bu...
Seeking excess returns under a posted price mechanism: Evidence from a peer‐to‐peer lending market
The Manchester School, 2020
This study examines the performance of a new online peer-to-peer (P2P) lending platform in China that relies on non-expert individuals to screen for loans. Using the bank deposit rate as a benchmark, positive excess returns exist under the posted price mechanism, which indicates that P2P markets provide lenders with adequate profit opportunities to compensate for investment risks. Moreover, we find that loans with higher excess returns are more likely to be funded and are bid on more quickly than other loans. Finally, voluntarily disclosed soft information in the listing's description plays a significant moderating role in the lenders' decision-making process. Borrowers who promise to repay on time are more likely to be funded and to be funded faster, but those who claim economic hardship have a lower probability of being funded. Our results provide evidence that lenders have the ability to seek excess returns in P2P lending markets and highlight that aggregating the views of peers can improve market efficiency.