It is widely recognised that the ability of e-commerce businesses to predict conversion probability, i.e., acceptance probability, is critically important in today's business environment. While the issue of conversion prediction based on browsing data in various e-commerce websites is broadly...

This paper takes a deep learning approach to understand consumer credit risk when e-commerce platforms issue unsecured credit to finance customers' purchases. The "NeuCredit" model can capture both serial dependences in multi-dimensional time series data when event frequencies in each dimension...

The existence of peer effect on financial decision is well documented in the literature. However, little is known about the peer effect on default choice of consumer credit. We fill this gap by using a novel data and research design constructed from a cash loan platform in China. We find the...

This paper exploits a detailed new dataset with comprehensive financial and consumption information to investigate the relationship between a cash-loan borrower's access to credit and their respective consumption response. In particular, we test whether consumption among borrowers with a high...

We report the results of a longitudinal intervention with students across five universities in China designed to reduce online consumer debt. Our research design allocates individuals to either a financial literacy treatment, a self-control training program, or a zero-touch control group....