Determinants of Successful Loan Application on Peer-to-Peer Lending Market

Gavurová, Beata; Dujcak, Martin; Kováč, Viliam; Kotásková, Anna

doi:10.14254/2071-789x.2018/11-1/6

Cited by 21 publications

(19 citation statements)

References 25 publications

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“…This means that investors prefer to finance lower loan requests as they consider higher ones more risky. Gavurova et al (2018) verified the general conclusions from recent studies; however, their analysis was carried out on the portfolio table of Bondora, which is a European platform, originating in Estonia. Bondora allows lending across borders, thus the results mostly reflected the behaviour of European investors from the region.…”

Section: Determinants Of Funding Successsupporting

confidence: 82%

An overview of peer-to-peer lending

Ölvedi¹

2020

Economy & finance

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In recent years, various alternative funding methods have appeared on the financial market, available to a broad range of potential borrowers. One form of this new stream is peer-to-peer lending (P2P). Despite this business model being relatively new, a large number of platforms have appeared worldwide and the market has shown robust expansion. On the one hand, these platforms have a number of competitive advantages compared to the traditional banking sector, such as low administrative costs, efficient operations and cheap loans for borrowers, coupled with higher returns for investors. From another perspective, several risk factors have arisen due to the nature of this business model; for example, the limited consequences in case of default, the lack of institutional guarantees, and insufficient monitoring. Recent views suggest that the emerging trend of peer-to-peer platforms will be challenging for regulators, as well as for commercial banks, which might consider them as potential competitors in future. The purpose of this paper is to highlight the relevance of this growing sector through recent financial statistics, including lending volumes of the main players and the geographical expansion of the market. Furthermore, the study presents the main features of this alternative funding method, provides an overview of the growing literature on the subject, and presents the key findings.

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Section: Determinants Of Funding Successsupporting

confidence: 82%

An overview of peer-to-peer lending

Ölvedi¹

2020

Economy & finance

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“…However, as credit rating is not the actual credit score, those with low credit scores tend to select "borrow money" on platforms, thus causing an adverse selection problem (Freedman & Jin, 2008). In addition, debt to income ratio can remarkably influence investors' decision making, that is, the lower the debt to income ratio of a borrower, the easier for him/her to obtain a loan (Gavurova, Dujcak, Kovac & Kotaskova, 2018). As for character features of borrowers, existing studies show that age discrimination exists on P2P lending platforms; young people and the aged have difficulty in obtaining loans.…”

Section: Readability Of Loan Description With Loan Success Rate and Lmentioning

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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“…At present, most scholars use "hard information" to research borrowers' default behavior, while "soft information" is unlimited in its content [8][9][10]. Soft information can reduce the information asymmetry of both lenders to a certain extent [11][12][13]. Considering the size and speed of the global P2P loan market, even a slight improvement, such as 1%, in credit risk assessment performance may lead to a significant reduction in the losses caused by default events in the P2P loan market [14].…”

Section: Introductionmentioning

confidence: 99%

How Does the Urgency of Borrowing in Text Messages Affect Loan Defaults? Evidence from P2P Loans in China

Hong

Yuan

Zhou

2021

Security and Communication Networks

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In P2P loans with information asymmetry, the text information described by the borrower plays an important role in alleviating the information asymmetry between borrowers and lenders. To explore the borrowing described in text information and its relationship with default behavior, this article selects credits from April 2014 to October 2016 as the repayment period and studies default data. This is performed based on the length of the excavated text, purpose of the loan, repayment ability, willingness to reimburse, five text variables, and degree of loan urgency. The empirical results show that text length has a significant negative correlation with the default probability of borrowers. Different loan purposes have different default risks. Interestingly, the more urgent a loan is, the more likely the borrower is to default. However, repayment ability information and repayment willingness information have no significant effect on default behavior. In addition, the Nagelkerke R2 improved by nearly 3% in the logistic regression model with the addition of text variables. In short, fully excavating loan description information is helpful in reducing the risk of loan default.

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Determinants of Successful Loan Application on Peer-to-Peer Lending Market

Cited by 21 publications

References 25 publications

An overview of peer-to-peer lending

An overview of peer-to-peer lending

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

How Does the Urgency of Borrowing in Text Messages Affect Loan Defaults? Evidence from P2P Loans in China

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