Data‐driven optimization of peer‐to‐peer lending portfolios based on the expected value framework

Byanjankar, Ajay; Mezei, József; Heikkilä, Markku

doi:10.1002/isaf.1490

Cited by 7 publications

(6 citation statements)

References 29 publications

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“…The theoretical criteria are met by using the most informative ratios to assess the creditworthiness of financial companies and credit unions (Byanjankar et al, 2021). To achieve the possibility of comparing the results of calculations, the creditworthiness indicators should be expressed in the same values.…”

Section: Introductionmentioning

confidence: 99%

Retracted: Internal procedures of the risk‐oriented lending process in the bank

Ushanov

2022

Risk Manage Insurance Review

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Information about the financial condition of financial institutions is the basis for assessing the risk of their lending. In the conditions of economic instability, the validity and effectiveness of management decisions significantly depend on the quality of financial and analytical calculations. To take into account, the specifics of the activities of various types of financial institutions when assessing the risk of their lending, the author put forward a hypothesis about the advisability of clarifying the composition of indicators used to assess the creditworthiness of borrowers. The analysis of the creditworthiness of financial companies and credit unions has been carried out. It was found that, during 2020–2021, no financial institution had the highest creditworthiness; at the same time, financial companies were more capable of meeting loan obligations than credit unions. A system of quantitative and qualitative indicators has been formed using correlation and factor analysis to assess the risk of lending to the activities of financial companies and credit unions. Certain indicators are suitable for integral assessment, and, therefore, create the basis for improving the methodological approach to assessing the risk of lending to financial institutions.

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Section: Introductionmentioning

confidence: 99%

Retracted: Internal procedures of the risk‐oriented lending process in the bank

Ushanov

2022

Risk Manage Insurance Review

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“…Phase 2: The study analyzes the critical success factors of online loan platform management in Thailand by designing a theoretical reference query (using confirmatory factor analysis CFA) to statistically confirm elements or indicators and decide whether they support the hypothesis [54,59,60]. The trust of lenders as measured by the CFA analysis method has five steps: parameter estimation, verifying model consistency, model fitting, and interpretation of the analysis results.…”

Section: Discussionmentioning

confidence: 99%

“…Our application development team has developed a P2P lending platform development plan in the form of a software development plan that is divided into the following sections: scope, analysis/software requirements, design, development, testing, unit testing, and link UX/UI. The system architecture and the project of developing a platform and a P2P lending system through a P2P lending web application has three main components [48,[53][54][55].…”

Section: Peer-to-peer Lending Platform Development Applicationmentioning

confidence: 99%

Success Factors Influencing Peer-to-Peer Lending to Support Financial Innovation

Chulawate

Kiattisin

2023

Sustainability

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The purpose of this study is to identify success factors that are conducive to developing the ability to create financial innovation within developing countries for the sake of sustainability. The purpose of this research is to contribute to the identification of success factors. The case study involves a peer-to-peer lending (P2P Lending) business operator in Thailand and focuses on the lender perspective. The results consist of 13 potential factors driving financial innovation in process improvement. The study collected data from 300 respondents through a structured questionnaire. The structural equation model was used to analyze the data via Mplus version 7. In order to gain a better understanding, we emphasize that each country’s financial business may show different success factors due to different situations and environments, which might pose a challenge when drawing conclusions from the survey and building sustainability in the financial industry. The research summarizes the factors of success in 3 contexts with 13 factors; namely, the risk context consists of a higher interest rate, inflation increase, macroeconomics, regulation laws, and legal, liquidity, and finance and credit status. The trust context includes demographic characteristics, biological characteristics, and an individual’s reputational capital, and the lender perspective information context includes loan delinquencies, funded loans, politics, and culture. According to our results, the investor or lender will benefit from bringing concepts and methods that involve adopting international loans.

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“…They also claimed to have implemented machine learning practices to reinforce their credit scoring system. Indeed, machine learning has been studied to give a favorable outcome for credit scoring, one of them is the optimization of the portfolio of borrowers to aid lenders to get the best return for their investments (Byanjankar et al , 2021).…”

Section: Findings and Discussion Desk Researchmentioning

confidence: 99%

The bane of P2P lending: credit scoring governance on the ASEAN fintech triumvirate

Rosdini

Wahyuni²,

Sari³

2022

JSTPM

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Purpose This study aims to explore credit scoring regulations, governance, variables and methods used by peer-to-peer (P2P) lending platforms in key players of the Association of Southeast Asian Nations (ASEAN) region’s P2P, Indonesia, Malaysia and Singapore. Design/methodology/approach This study explores the P2P Lending characteristics of the three countries using qualitative literature review, interview, focus group discussion and desk research. Findings This study concludes that the credit scoring variables used by the countries’ companies are almost the same. Key drivers of the differences are countries’ regulations, management/business core value and credit scoring data processing methods. Practical implications Ultimately, this research provides a comprehensive view for investors, businesses and researchers on the topic of ASEAN credit scoring governance and will help them navigate the complexities and improve their awareness on the importance of credit scoring governance in P2P lending companies. Originality/value This research provides an in-depth perspective on how P2P lending companies, credit scoring governance and regulations in the biggest three countries in Southeast Asia.

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Data‐driven optimization of peer‐to‐peer lending portfolios based on the expected value framework

Cited by 7 publications

References 29 publications

Retracted: Internal procedures of the risk‐oriented lending process in the bank

Retracted: Internal procedures of the risk‐oriented lending process in the bank

Success Factors Influencing Peer-to-Peer Lending to Support Financial Innovation

The bane of P2P lending: credit scoring governance on the ASEAN fintech triumvirate

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