Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending

Lin, Ming-Chyuan; Prabhala, Nagpurnanand; Viswanathan, Siva

doi:10.2139/ssrn.1355679

Cited by 263 publications

(421 citation statements)

References 75 publications

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“…group membership) improves funding success and reduces interest rates and default probability, while Freedman and Jin (2008) find that loans endorsed by friends, and bids, show fewer missed bids have fewer missed) payments and higher rates of return. Using a sample of Prosper listings, Lin et al (2013) examine the role that friendship networks played in the outcomes of loans on the P2P market. They find that the friendship can serve as an informational boost to a borrower's credit quality, increase the probability of successful funding, and reduce the interest rate of loans and default risk on funded loans.…”

Section: Related Literature Reviewmentioning

confidence: 99%

“…Therefore, we expect an inversely U-shaped relationship between the interest rates and the probability of funding success. Following Lin et al (2013), we include the interest rate (LISTRATE) and its quadratic term (LISTRATE2) in our regressions to capture this relationship. We also incorporate two additional variables to measure the loan amount requested (LSIZE) and loan length (LLENGHT) which are related to risks and affect the lenders' lending decisions (Herzenstein and Andrews, 2008;Chen et al, 2009).…”

Section: Data and Variablesmentioning

confidence: 99%

“…One of the major problems of P2P lending is asymmetric information (Freedman and Jin, 2008;Lin et al, 2013). This problem is more pronounced in the Chinese P2P lending market due to the lack of reliable and comprehensive credit information.…”

Section: Data and Variablesmentioning

confidence: 99%

“…Herzenstein and Andrews, 2008;Iyer et al, 2009;Dorfleitner et al, 2016) and friendship and group networks (e.g. Chen et al, 2009;Lin, 2013;Liu et al, 2015;Bellefamme et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Freedman and Jin, 2008;Weiss et al 2010;Pope and Sydnor, 2011;Ravina, 2008;Lin et al 2013;Iyer et al 2016) and crowdfunding, another type of alternative financing activities (e.g. Belleflamme et al 2015;Colombo et al 2015;.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Who can get money? Evidence from the Chinese peer-to-peer lending platform

2017

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This paper explores how borrowers' financial and personal information, loan characteristics and lending models affect peer-to-peer (P2P) 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 who own 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 unique offline process in the Chinese P2P online lending platform exerts significant influence on the lending decision. We discuss the implications of our results for the design of big databased lending markets.

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Section: Related Literature Reviewmentioning

confidence: 99%

Section: Data and Variablesmentioning

confidence: 99%

Section: Data and Variablesmentioning

confidence: 99%

“…Herzenstein and Andrews, 2008;Iyer et al, 2009;Dorfleitner et al, 2016) and friendship and group networks (e.g. Chen et al, 2009;Lin, 2013;Liu et al, 2015;Bellefamme et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Who can get money? Evidence from the Chinese peer-to-peer lending platform

2017

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How different Are crowdfunders? Examining archetypes of crowdfunders

Lin

Boh

2019

Asso for Info Science & Tech

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We unpack the complexities of the crowdfunder community by identifying different archetypes of crowdfunders funding technology projects on Kickstarter. com. Drawing on the extant literature on innovation adoption and opinion leadership, we propose two dimensions of crowdfunders that capture the heterogeneity in crowdfundersʼ behavior: opinion leadership and interest specialization of crowdfunders. Using a set of variables representing these two dimensions, our analysis revealed five distinct archetypes of crowdfunders: the Vocal Actives, the Silent Actives, the Focused Enthusiasts, the Trend Followers, and the Star Seekers, who each adopted distinct crowdfunding strategies. We established external and criterion-related validity of the cluster solutions in multiple ways. Our results suggest that the composition of crowdfunders is complex, even within a single platform.

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Geography and social network influence on crowdfunding a French microbrewery

et al. 2022

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The objective of this article is to explore the influence of home bias and the moderating role of social networks (and more particularly family and friends -F&F) in the crowdfunding of a microbrewery in a French region (a lucrative business that uses a territorial solidarity process). We have chosen the case study as methodology to show that neither home bias nor F&F have a significant influence on amounts paid by individuals in crowdfunding. The results are specific to the case studied and are comparable to those of social enterprise. They explain but also justify the behavioural diversity crowdfunding can induce.

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Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending

Cited by 263 publications

References 75 publications

Who can get money? Evidence from the Chinese peer-to-peer lending platform

Who can get money? Evidence from the Chinese peer-to-peer lending platform

How different Are crowdfunders? Examining archetypes of crowdfunders

Geography and social network influence on crowdfunding a French microbrewery

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