Determinants and Consequences of Herding in P2P Lending Markets

In this paper, we are interested in the factors that influence herding behavior in P2P lending marketplaces. We are using data from Prosper.com to examine whether internal market specific factors and external economic factors influence the amount of herding exhibited in the market. We also investigate what consequences herding has and how marketplace participants can benefit or suffer from herding behavior in the marketplace. Based on previous models of herding in P2P lending, we calculate a herding measure over time. This herding measure is the basis for our analyses. Our preliminary analyses show support that internal factors measuring uncertainty, lenders experience, and search costs in the market influence herding. We receive inconclusive results for external factors measuring uncertainty, volatility, and bullishness in the marketplace’s economic environment. Herding has several implications for borrowers and lenders including potentially lower interest rates for borrowers but fewer completed listings

THE EFFECTS OF WEBPAGE COLOR ON LENDERS’ DECISIONS IN ONLINE P2P LENDING: A CONSTRUAL LEVEL THEORY PERSPECTIV

In recent years, P2P (peer-to-peer) lending as the most popular innovative business model of Internet finance, has received wide attentions from government, industry, and researchers. Prior academic attention has been devoted to the investigation of factors that may affect lenders’ bidding strategies. In this study, based on the construal level theory, we examine the effect of webpage color (warm vs. cool) on lenders’ preference between acceptable benefit and risk when they decide to make a bid. A series of laboratory experiments are designed to test our proposed hypotheses

Determinants of default in p2p lending: the Mexican case

P2P lending is a new method of informal finance that uses the internet to directly connect borrowers with on-line communities. With a unique dataset provided by Prestadero, the largest on-line lending platform with national presence in Mexico, this research explores the effect of credit scores and other variables related to loan and borrower´s traits, in determining default behavior in P2P lending. Moreover, using a logistic regression model, it tested whether investors might benefit from screening loan applicants by gender after controlling for loan quality. The results showed that information provided by the platform is relevant for analyzing credit risk, yet not conclusive. In congruence with the literature, on a scale going from the safest to the riskiest, loan quality is positively associated with default behavior. Other determinants for increasing the odds of default are the payment-to-income ratio and refinancing on the same platform. On the contrary loan purpose and being a female applicant reduce such odds. No categorical evidence for differential default behavior was found for gender´s case-discrimination, under equal credit conditions. However it was found that controlling for loan quality, women have longer loan survival times than men. This is one of the first studies about debt crowdfunding in Latin America and Mexico. Implications for lenders, researchers and policy-makers are also discussed

Judging Online Peer-To-Peer Lending Behavior: An Integration of Dual System Framework and Two-Factor Theory

The past decade has witnessed a growing number of business models that facilitate economic exchanges between individuals with limited institutional mediation. One of the important innovative business models is online peer-to-peer (P2P) lending, which has received widely attention from government, industry, investors, and researchers. Based on dual system framework and two-factor theory, this research proposes a research model to investigate the role of various signals from the P2P platform in affecting lender’s investment decisions. With data collected from PPDAI, a popular Chinese P2P lending site, we test the proposed model with logistic regression and hierarchical linear model. The results reveal that most of the factors perform significantly in lenders’ decision making. We also find the specific information of an auction itself is more important than borrower’s characteristics to a large degree. Finally, the research emphasizes that bid number performs well in moderating most of the relationships between variables

Social Networks in Online Peer-to-Peer Lending: The Case of Event-Type Ties as Pipes and Prisms

A considerable amount of academic research on crowdfunding has highlighted the importance of online social networks to crowdfunding success. Despite findings from these early studies, the focus of the extant literature has been on more persistent state-type ties such as friendship. In the current research, we examine how borrower-partner and borrower-team event-type ties affect lender behavior and loan success in online peer-to-peer (P2P) lending. Our empirical results using a multilevel mixed effects model reveal that borrower-team networks function as pipes that facilitate the flow of information and prospective lenders while borrower-partner ties function as prisms that signal borrowers’ pressing financial need. Our results highlight the importance of establishing lending teams on crowdfunding platforms to enhance lender contribution

Crowdlending: mapping the core literature and research frontiers

[EN] Peer-to-peer (P2P) lending uses two-sided platforms to link borrowers with a crowd of lenders. Despite considerable diversity in crowdlending research, studies in this area typically focus on several common research topics, including information asymmetries, social capital, communication channels, and rating-based models. This young research field is still expanding. However, its importance has increased considerably since 2018. This rise in importance suggests that P2P lending may offer a promising new scientific research field. This paper presents a bibliometric study based on keyword co-occurrence, author and reference co-citations, and bibliographic coupling. The paper thus maps the key features of P2P lending research. Although many of the most cited papers are purely financial, some focus on behavioral finance. The trend in this field is toward innovative finance based on new technologies. The conclusions of this study provide valuable insight for researchers, managers, and policymakers to understand the current and future status of this field. The variables that affect new financial contexts and the strategies that promote technology-based financial environments must be investigated in the future.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.Ribeiro-Navarrete, S.; Piñeiro-Chousa, J.; López-Cabarcos, MÁ.; Palacios Marqués, D. (2022). Crowdlending: mapping the core literature and research frontiers. Review of Managerial Science. 16(8):2381-2411. https://doi.org/10.1007/s11846-021-00491-82381241116

Crowdlending: mapping the core literature and research frontiers

Peer-to-peer (P2P) lending uses two-sided platforms to link borrowers with a crowd of lenders. Despite considerable diversity in crowdlending research, studies in this area typically focus on several common research topics, including information asymmetries, social capital, communication channels, and rating-based models. This young research field is still expanding. However, its importance has increased considerably since 2018. This rise in importance suggests that P2P lending may offer a promising new scientific research field. This paper presents a bibliometric study based on keyword co-occurrence, author and reference co-citations, and bibliographic coupling. The paper thus maps the key features of P2P lending research. Although many of the most cited papers are purely financial, some focus on behavioral finance. The trend in this field is toward innovative finance based on new technologies. The conclusions of this study provide valuable insight for researchers, managers, and policymakers to understand the current and future status of this field. The variables that affect new financial contexts and the strategies that promote technology-based financial environments must be investigated in the futureOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer NatureS

Credit Risk Management of P2P Network Lending

This article first studies the literature of P2P online loans, including online loans, credit risk factors and models, and summarizes the current status of P2P and credit risk assessment management in China. Based on the loan data of domestic P2P lending platforms, this paper conducts an empirical study on credit risk assessment. This study uses random forest importance assessment and logistic regression classification for credit risk assessment to identify loan targets with higher probability of default and improve overall loan quality. This research used 10,930 loan data, based on 26 fields, and finally selected 20 model variables to participate in credit risk quantification through feature structure and feature analysis. The final modelling test results show that the model screening accuracy rate is 73.3%, indicating that this model has a good performance in the credit risk quantification of borrowers

The Power of Words in Crowdfunding

In this chapter, the authors first provide an overview of the crowdfunding phenomenon. Through the literature review of crowdfunding success factors in the four models, the authors then summarize that the current entrepreneurial research focused on success factors has failed to sufficiently examine how the power of words would affect crowdfunding. Therefore, the authors propose that non-verbal and verbal cues are crucial to entrepreneurial financing success. Based on the insufficient research related with those cues, especially the non-verbal ones, the authors open an area of study on non-verbal and verbal cues in the entrepreneurial financing process by conducting and writing this chapter

Internet Finance: A Systematic Literature Review and Bibliometric Analysis

Internet finance has gained growing popularity in internet plus environment. While various problems have emerged, and hindered the sustainable growth of internet finance industry. Thus, a summary of existent research and directions for future study are expected. However, few comprehensive literature reviews has been published. This paper presents a thorough bibliometric and network analysis following a systematic literature review methodology. The analysis begins by identifying 331 published studies in Web of Science. Prolific authors, institutions and nations are identified by rigorous bibliometric tools. Based on citation and co-citation analysis, influential papers from different time periods are identified. Established and emergent research clusters are identified for topological analysis by coupling analysis. Future research opportunities are pointed out