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....

We analyze the information content of the digital footprint – information that people leave online simply by accessing or registering on a website – for predicting consumer default. We show that even simple, easily accessible variables from the digital footprint match the information content...

We analyze the information content of the digital footprint – information that people leave online simply by accessing or registering on a website – for predicting consumer default. Using more than 250,000 observations, we show that even simple, easily accessible variables from the digital...

We analyze the information content of the digital footprint - information that people leave online simply by accessing or registering on a website - for predicting consumer default. Using more than 250,000 observations, we show that even simple, easily accessible variables from the digital...

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 emergence of consumer credit issued on E-commerce platforms poses a new challenge for financial regulators. In the lens of a stylized model, this paper analyzes E-commerce consumer credit's economics and welfare implications. It highlights four points that warrant the particular attention of...