Specialized Lending when Big Data Hardens Soft Information

Finance Seminar joint with LawFin Research Seminar

Abstract (Joint with Zhiguo Her and Jing Huang):

We study the effects of hardening soft information on credit market competition with special-
ized lending. Our framework considers multi-dimensional information and distinguishes between
the breadth (information span) and quality (signal precision) of data, capturing the emerging
trend in fintech lending where traditionally subjective (“soft”) information becomes more ob-
jective and concrete (“hard”). In the model, two banks equipped with similar data processing
systems possess hard signals about the borrower’s quality, and the specialized bank further
interacts with the borrower, allowing it to access soft signals. Hardening soft information lev-
els the playing field by reducing the winner’s curse for the non-specialized bank from the soft
signal. In contrast, increasing the precision or correlation of hard information strengthens the
informational advantage of the specialized bank.