We explore whether behavioral biases impede the effective processing and interpretation of soft information in private lending. Taking advantage of the internal reporting system of a large federal credit union, we delineate three important biases likely to affect the lending process: (1) limited...

By leveraging machine-learning algorithms and using nontraditional digital data derived primarily from borrowers’ mobile devices, digital lenders have vastly expanded access to credit in developing economies for millions of individuals without a prior credit history. At the same time,...