Pricing mechanisms in the online Peer-to-Peer lending market

Ma, Benjiang; Zhou, Zhenglong; Hu, Fengying

doi:10.1016/j.elerap.2017.10.006

Cited by 16 publications

(8 citation statements)

References 26 publications

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“…Nevertheless, in certain social groups, there is an indication that P2P Lending services are not in such great demand, and this includes corporate financing (Chen, Zhou, and Wan 2016). These findings are supported by the perspective of lenders in the study by (Ma, Zhou, and Hu 2017). The risks of P2P Lending from the perspective of lenders are also high and need to be managed properly, in particular concerning the risk related to the historical data of prospective customers and the lack of guarantee needed for financing (Liu et al 2019).…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 65%

“…This assumption is formulated from a number of indicators, such as high interest costs, lack of transparency in the appraisal process, and security of customer data (Lenz 2016;Zhu 2018). In addition, the avoidance of risk, in particular relating to financing amounts and uncertain interest levels, is a strategic matter that requires the attention of lenders, as discussed in various studies (Chen, Zhou, and Wan 2016;Ma, Zhou, and Hu 2017). Therefore, the fourth hypothesis developed H4: The decision not to use P2P Lending services is greater and more significant than the decision to use the service, when taking into consideration the perception of risk.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

“…Research on the subject of P2P Lending has previously been carried out by numerous scholars, including (Tao, Dong, and Lin 2017;Lin, Prabhala, and Viswanathan 2011;Lenz 2016;Gimpel, Rau, and Röglinger 2018;Stern, Makinen, and Qian 2017;Ma, Zhou, and Hu 2017;Chen, Zhou, and Wan 2016;Adriana and Dhewantoa 2018;Gibilaro 2018;Jie et al 2018;Zhu 2018;Liu et al 2019). However, these studies do not analyze the considerations and perception of opportunity or risk when making a decision to use, not to use, or be uncertain about Fintech.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Fintech Based Peer to Peer Lending: An Opportunity or a Threat?

Setyaningsih¹,

Murti

Nugrahaningsih

2019

REAKSI

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Peer-to-peer lending is like a double-edged sword, on one side providing a solution, on the other posing a threat or risk for borrower's. This quantitative research analyzed 62 respondents. The finding is that potential customers are more likely to use this service when they perceive that platform is a good opportunity to serve their financial needs. It can be stated the decision to delay using this service has a greater tendency for people to still use it in the future. Another interesting result shows the choice remains consistent even though respondents take into consideration the risks of platform.

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Section: Literature Review and Hypothesis Developmentmentioning

confidence: 65%

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fintech Based Peer to Peer Lending: An Opportunity or a Threat?

Setyaningsih¹,

Murti

Nugrahaningsih

2019

REAKSI

View full text Add to dashboard Cite

show abstract

“…Emekter et al (2015) stated that higher interest rates charged on the high-risk borrowers are not enough to compensate for higher probability of default and claimed that, in order to sustain the business, LendingClub must attract borrowers with a high FICO score and high-income. Ma et al (2017) studied different pricing mechanisms in peer-to-peer lending market, under the consideration of lenders' risk appetite. They have included the borrower pricing mechanism (BPM), the auction pricing mechanism (APM), which is Prosper's pricing mechanism before 2010, and the platform pricing mechanism (PPM), which Prosper used after a regime change.…”

Section: Related Work On Peer-to-peer Lendingmentioning

confidence: 99%

Peer-To-Peer Lending: Classification in the Loan Application Process

Wei

Gotoh

Uryasev

2018

Risks

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This paper studies the peer-to-peer lending and loan application processing of LendingClub. We tried to reproduce the existing loan application processing algorithm and find features used in this process. Loan application processing is considered a binary classification problem. We used the area under the ROC curve (AUC) for evaluation of algorithms. Features were transformed with splines for improving the performance of algorithms. We considered three classification algorithms: logistic regression, buffered AUC (bAUC) maximization, and AUC maximization.With only three features, Debt-to-Income Ratio, Employment Length, and Risk Score, we obtained an AUC close to 1. We have done both in-sample and out-of-sample evaluations. The codes for cross-validation and solving problems in a Portfolio Safeguard (PSG) format are in the Appendix. The calculation results with the data and codes are posted on the website and are available for downloading.

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“…Credit risk is the possible loss a bank or other lender suffers after offering a loan to a borrower. They include the actual risk of the borrower defaulting on the loan on time and the potential risk of default due to a decrease in credit score [3][4][5][6] or a reduction in the borrowers' ability to repay, and the lending platform getting profitable [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Decentralized trustworthiness score management with smart contracts on the trustlend platform

Uriawan,

Badr,

Hasan

et al. 2023

IET Blockchain

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The personal lending marketplace, known as Peer‐to‐Peer (P2P) lending, has increased globally. However, providing unsecured loans to peers without requiring collateral remains a challenge. A platform called TrustLend is proposed to enable trustworthy transactions in the personal lending application. The platform attempts to eliminate or minimize the collateral requirement. The trustworthiness score adds to this platform's variable selection rules and can help lenders decide on reliable candidates as borrowers. The prototype implementing the TrustLend platform based on Ethereum smart contracts that use the trustworthiness score is also described and it is illustrated with a Decentralized Application (DApp) case study and customized smart contracts. The prototype demonstrates fundamental features and supports borrowers, lenders, and recommenders in establishing proposals and approvals. Finally, the prototype shows how end‐users can easily access loans with reduced collateral without hidden costs and swift transactions.

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Pricing mechanisms in the online Peer-to-Peer lending market

Cited by 16 publications

References 26 publications

Fintech Based Peer to Peer Lending: An Opportunity or a Threat?

Fintech Based Peer to Peer Lending: An Opportunity or a Threat?

Peer-To-Peer Lending: Classification in the Loan Application Process

Decentralized trustworthiness score management with smart contracts on the trustlend platform

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