Addressing Information Asymmetries in Online Peer-to-Peer Lending

Cummins, Mark; Lynn, Theo; Bhaird, Ciarán Mac an; Rosati, Pierangelo

doi:10.1007/978-3-030-02330-0_2

Cited by 10 publications

(8 citation statements)

References 43 publications

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“…Information provided by P2P lending platforms is limited and usually insufficient for investors to properly assess whether borrowers are trustworthy and whether they can pay back loans . As a result, investors face high risks of adverse selection and moral risks (Cummins, Lynn, Mac an Bhaird & Rosati, 2019). Hence, long-term development of P2P loan market, to a great extent, depends on market participants' abilities to reduce information asymmetry with the help of effective information (Ye & Chen, 2017).…”

Section: Introductionmentioning

confidence: 99%

Can Readability of Loan Description Affect Loan Success Rate and Loan Cost?: A Textual Analysis of P2P Loan Description

Jiang

Fang

et al. 2020

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Text is an important form of information transfer. In a P2P (Peer-to-Peer) loan market with severe information asymmetry, loan descriptive information voluntarily written by a borrower may generate significant influence on investors’ decision-making. As an important language feature, readability determines whether the audience can accurately identify textual contents. To discuss the influence of readability of loan description on borrowing behaviors, the data of a Chinese P2P lending platform Renrendai during 2013–2017 were used in this study. Readability index of loan description was constructed through the textual analysis method, followed by an empirical verification of the influences of readability of loan description on loan success rate and loan cost. Results indicate that the readability of loan description in China’s P2P loan market can generate incremental information, and the readability of loan description has evident nonlinear relations with loan success rate and loan interest rate. Moreover, the readability of loan description presents a “reverse U-shaped” relation with loan success rate and a “U-shaped” relation with loan interest rate. Demographic information (gender and educational background) of borrowers will not influence investors’ feedback behaviors toward the readability of loan description. Conclusions provide empirical evidence for standardizing loan descriptive information on P2P lending platforms.

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Section: Introductionmentioning

confidence: 99%

Can Readability of Loan Description Affect Loan Success Rate and Loan Cost?: A Textual Analysis of P2P Loan Description

Jiang

Fang

et al. 2020

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“…Table 4 provides an overview of the funding provided through P2P lending platforms by region and segment. Zopa was the first P2P lending platform to be launched back in 2005 (Cummins et al 2019). Two other large US-based platforms, Prosper.com and LendingClub, followed in 2006 and 2007, respectively (Greiner and Wang 2009).…”

Section: Peer-to-peer Lendingmentioning

confidence: 99%

“…P2P lending is anything but new. Entrepreneurs have traditionally leveraged their personal network to raise capital (Berger and Udell 1998;Kotha and George 2012;Robb and Robinson 2014;Cummins et al 2019). Small loans are often provided by family members or friends on the basis of personal relationships rather than formal due diligence.…”

Section: Peer-to-peer Lendingmentioning

confidence: 99%

“…These informal transactions carry undeniable risks for both borrowers and lenders. Online P2P lending platforms have improved this process by providing online marketplaces that enable borrowers and lenders to transact directly with defined rules of engagement and by providing due diligence services that reduces the risk of default (Cummins et al 2019). In exchange for this, platforms charge a fee, typically a small percentage of the funded amount, paid by borrowers.…”

Section: Peer-to-peer Lendingmentioning

confidence: 99%

“…lenders) bear all the risk in P2P lending, and a key metric for them to evaluate platforms is default rate. As a result, (2017a, b, 2018a, b, c, d), Cummins et al (2019) the rejection rate at the application stage is quite high for risky borrowers, and capital is more likely to flow towards borrowers who are already "bankable" (Tang 2019).…”

Section: Peer-to-peer Lendingmentioning

confidence: 99%

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Digital technologies are transforming entrepreneurial finance. Near-ubiquitous access to the Internet, platformisation, and advances in cloud computing, machine learning and artificial intelligence, and blockchain are changing the sources, basis, and quantum of funding in ways that were unimaginable at the turn of the century. This chapter outlines the changes to the market for entrepreneurial finance from the perspective of structure and participants. The key sources and characteristics of alternative sources of finance available to entrepreneurs, including start-ups, are presented. Two online alternative finance sources, crowdfunding and token offerings, are discussed in greater detail. These are illustrated with case studies. This chapter concludes with recommendations and a discussion of practical implications.

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Addressing Information Asymmetries in Online Peer-to-Peer Lending

Cited by 10 publications

References 43 publications

Can Readability of Loan Description Affect Loan Success Rate and Loan Cost?: A Textual Analysis of P2P Loan Description

Can Readability of Loan Description Affect Loan Success Rate and Loan Cost?: A Textual Analysis of P2P Loan Description

New Sources of Entrepreneurial Finance

Digital economy, agglomeration, and entrepreneurship in Chinese cities

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