Information-Based Pricing in Specialized Lending

Kristian Blickle, Zhiguo He (), Jing Huang and Cecilia Parlatore
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Jing Huang: Texas A&M U
Cecilia Parlatore: New York U

Research Papers from Stanford University, Graduate School of Business

Abstract: We study specialized lending in a credit market competition model with private information. Two banks, equipped with similar data processing systems, possess "general" signals regarding the borrower's quality. However, the specialized bank gains an additional advantage through further interactions with the borrower, allowing it to access "speciliazed" signals. In equilibrium, both lenders use general signals to screen loan applications, and the specialized lender prices the loan based on its specialized signal conditional on making a loan. This private-information-based pricing helps deliver the empirical regularity that loans made by specialized lenders have lower rates (i.e., lower winning bids) and better ex-post performance (i.e., lower non-performing loans). We show the robustness of our equilibrium characterization under a generalized information structure, endogenize the specialized lending through information acquisition, and discuss its various economic implications.

JEL-codes: G21 L13 L52 O33 O36 (search for similar items in EconPapers)
Date: 2023-12
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Working Paper: Information-Based Pricing in Specialized Lending (2024)
Working Paper: Information-Based Pricing in Specialized Lending (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:ecl:stabus:4140

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