Information Span and Credit Market Competition

Zhiguo He (hezhg@stanford.edu), Jing Huang and Cecilia Parlatore

No 33141, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We develop a credit market competition model that distinguishes between the information span (breadth) and signal precision (quality), capturing the emerging trend in fintech/non-bank lending where traditionally subjective (“soft”) information becomes more objective and concrete (“hard”). In a model with multidimensional fundamentals, two banks equipped with similar data processing systems possess hard signals about the borrower's hard fundamentals, and the specialized bank, who further interacts with the borrower, can also assess the borrower's soft fundamentals. Increasing the span of the hard information hardens soft information, enabling the data processing systems of both lenders to evaluate some of the borrower's soft fundamentals. We show that hardening soft information levels the playing field for the non-specialized bank by reducing its winner's curse. In contrast, increasing the precision or correlation of hard signals often strengthens the informational advantage of the specialized bank.

JEL-codes: G21 L13 L52 O33 O36 (search for similar items in EconPapers)
Date: 2024-11
New Economics Papers: this item is included in nep-ban, nep-com, nep-fdg and nep-ind
Note: CF IO PR
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