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P2P lending is a new method of informal finance that uses the internet to directly connect borrowers with on-line communities. With a unique dataset provided by Prestadero, the largest on-line lending platform with national presence in Mexico, this research explores the effect of credit scores and other variables related to loan and borrower´s traits, in determining default behavior in P2P lending. Moreover, using a logistic regression model, it tested whether investors might benefit from screening loan applicants by gender after controlling for loan quality. The results showed that information provided by the platform is relevant for analyzing credit risk, yet not conclusive. In congruence with the literature, on a scale going from the safest to the riskiest, loan quality is positively associated with default behavior. Other determinants for increasing the odds of default are the payment-to-income ratio and refinancing on the same platform. On the contrary loan purpose and being a female applicant reduce such odds. No categorical evidence for differential default behavior was found for gender´s case-discrimination, under equal credit conditions. However it was found that controlling for loan quality, women have longer loan survival times than men. This is one of the first studies about debt crowdfunding in Latin America and Mexico. Implications for lenders, researchers and policy-makers are also discussed.
