We analyze the determinants of the level of interest rates related to business loans traded on digital crowdlending platforms. We consider one of the leading platforms in France and collect-ed original data on all the projects financed via this platform. On that platform, interest rates are set by the crowd of investors through a reverse auction process. We show that the loan characteristics and the scoring provided by the platform significantly influences the interest rate. However, though financial ratios are used traditionally to estimate credit risk, those ratios do not exhibit significant influence. Besides, we analyze the impact of the recent implementation of an automated auction mechanism. This implementation seems to have a large impact on both auction duration and on the determinants of interest rate. This suggests that use of a robot im-pacts on price and saving allocation on this platform-based credit market.
Darmon, Eric; Oriol, Nathalie; and Rufini, Alexandra, "LENDING ROBOTS AND HUMAN CROWDS: INTEREST RATE DETERMINATION ON A REVERSE AUCTION PLATFORM" (2018). Research Papers. 45.