Abstract
Using a robust textual analytic method, we decompose the P2P loan description into common and distinctive contents, which contain general and unique information provided by borrowers. We then investigate the role of the distinctive content in affecting P2P lending decisions and outcomes. Controlling for loan/borrower characteristics, loan applications with more distinctive content are more likely to be funded, and have larger amounts and longer maturity, but these loans carry higher interest rates and default probability. Overall, the evidence suggests that borrowers use self-reported loan descriptions to hype their loan applications rather than provide soft information to reduce information asymmetry.
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