From Credit Risk to Social Impact: On the Funding Determinants in Interest-Free Peer-to-Peer Lending
Based on a unique data set on US direct microloans, we study the funding determinants of interest-free peer-to-peer crowdlending aimed at borrowers in the US. By performing logistic regressions on funding success and Tobit regressions on the reversed funding time, the existence of a social underwriting by a third-party trustee and information in the description texts fostering the investors’ trust are shown to be the main predictors of successful funding. Regarding social impact, the possibility to empower women and groups of borrowers appeals to the investors, whereas empowerment of the family or community beyond the borrowers themselves appears to remain unappreciated. When examining the vulnerability of the borrowers as a predictor, the results manifest differences amongst the attitudes of the investors towards social impact. In the subsample of non-endorsed loans, the investors appear to prefer to support borrowers with an immigration background. In contrast, this is not the case with endorsed loans.
KeywordsText analysis Crowdlending Microfinance Funding probability Funding time
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