Comparison of Borrower Default Factors in Online Lending

Ginta Railiene ()
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Ginta Railiene: Kaunas University of Technology

A chapter in Consumer Behavior, Organizational Strategy and Financial Economics, 2018, pp 231-240 from Springer

Abstract: Abstract The factors describing the P2P borrower late payments and defaults are analyzed in the paper. Credit scoring and credit rating techniques are developed and used by finance institutions, but the features of online lending encourages to apply new practices in order to develop the decision support patterns for online lenders that are not professional investors. P2P platforms use credit scoring usually based on third party calculations, but they may be improved using wider soft information sources. The credit risk valuation of online borrowers is relatively new research area, where hard and soft information is used and assessed with different statistical methods, including the big data analysis. The paper aims to define the factors of online borrower late payments by systemizing the recent research findings and comparing them with results got from Lithuanian P2P platform data. The groups of factors researched are borrower and loan characteristics, borrower assessment and creditworthiness. The main findings allow to form specific propositions for lender decision support pattern suggesting the factors explaining the default: lower credit ratings and higher interest rates; greater loan amount and loan purpose for business, consolidation, home improvement and other; borrower indebtedness, employment length, age.

Keywords: Credit risk; Credit score; Default; Borrower assessment; Online lending; Peer to peer lending (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:eurchp:978-3-319-76288-3_17

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DOI: 10.1007/978-3-319-76288-3_17

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