Information Span in Credit Market Competition
We develop a credit market competition model that distinguishes between information span (breadth) and signal precision (quality), capturing the rise of fintech/nonbank lending where traditionally subjective (soft) information is transformed into objective (hard) data. Borrower quality depends on multidimensional fundamentals, assessed through hard or soft signals. Two banks observe private hard signals, but only the specialized bank receives a soft signal. Expanding the span of hard information enables the non-specialized bank to evaluate characteristics previously only available to the specialist, and reducing its winners curse. By contrast, greater precision of hard signals strengthens the specialized banks informational advantage.