This paper investigates the role of loan contract terms in the performance of consumer credit. Taking advantage of a sample of accepted and rejected consumer loans from a Czech commercial bank, I estimate the elasticity of loan demand and find that borrowers with a high probability of default...

This paper analyzes lenders' pricing strategies in the business-to-customer (B2C) unsecured loan market by using a proprietary dataset of approximately 3 million unsecured consumer loans from a B2C online retailer in China. We find that lenders' decisions to invite customers are based on...

This paper examines the disparity in default risk between vulnerable and non-vulnerable populations in consumer lending. We merge an exhaustive registry of loans granted in the financial system with microdata on vulnerable individuals applying for social programs. We estimate the sources of this...

On December 16th of 2015, the Fed initiated "liftoff", a critical step in the monetary normalization process. We use a unique panel dataset of 640,000 loan-hour observations to measure the impact of liftoff on interest rates, demand, and supply in the online primary market for uncollateralized...

Buy Now, Pay Later loans (BNPL) are an increasingly popular way to finance smallticket purchases. We provide new evidence on how BNPL influences regular bank credit markets, benefiting both lenders and borrowers through information production and learning. Using data from over one million...

Using a unique dataset on gaming and credit cards, we discover that default rates are higher among individuals who spend more, more frequently, and more erratically on video games, and among those who have more and more diverse games on their mobile devices. These results are less pronounced...

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...