Information asymmetries are known in theory to lead to inefficiently low credit provision, yet empirical estimates of the resulting welfare losses are scarce. This paper leverages a randomized experiment conducted by a large fintech lender to estimate welfare losses arising from asymmetric...

We exploit a natural experiment in the largest online consumer lending platform to provide the first evidence that loan terms, in particular maturity choice, can be used to screen borrowers based on their private information. We compare two groups of observationally equivalent borrowers who took...

We exploit a natural experiment in the largest online consumer lending platform to provide the first evidence that loan terms, in particular maturity choice, can be used to screen borrowers based on their private information. We compare two groups of observationally equivalent borrowers who took...

Consumer protection in financial markets in the form of information disclosure is high on governments agendas, despite the fact that the empirical evidence on its effectiveness is scarce. To measure the impact of Truth-in-Lending-Act-type disclosures on default and indebtedness, as well as of...

This chapter provides new evidence on borrowers' hidden information about their riskiness and its link to their impatience. To do so, I analyze consumer loans on the German platform Smava, which has a unique peer-to-peer lending process. Observationally identical but unobservably riskier...

This paper tests for incentive and selection effects in a subprime consumer credit market. We estimate the incentive effect of loan size on default using sharp discontinuities in loan eligibility rules. This allows us to estimate the magnitude of selection from the cross-sectional correlation...

We empirically study how the underlying riskiness of the pool of home equity line of credit originations is affected over the credit cycle. Drawing from the largest existing database of U.S. home equity lines of credit, we use county-level aggregates of these loans to estimate panel regressions...