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Information or Insurance? On the Role of Loan Officer Discretion in Credit Assessment

Author

Listed:
  • Martin Brown

    (University of St. Gallen)

  • Matthias Schaller

    (University of St. Gallen)

  • Simone Westerfeld

    (University of Applied Sciences Northwestern Switzerland)

  • Markus Heusler

    (Risk Solution Network AG)

Abstract

We employ a unique dataset of 6,669 credit assessments for 3,542 small businesses by nine banks using an identical rating model over the period 2006-2011 to examine (i) to what extent loan officers use their discretion to smooth credit ratings of their clients, and (ii) to assess whether this use of discretion is driven by information about the creditworthiness of the borrower or by the insurance of clients against fluctuations in lending conditions. Our results show that loan officers make extensive use of their discretion to smooth clients' credit ratings: One in five rating shocks induced by changes in the quantitative assessment of a client is reversed by the loan officer. This smoothing of credit ratings is prevalent across all rating classes, is independent of whether the borrower experiences a positive or a negative rating shock, and is independent of whether the shock is firm-specific or market-related. We find that discretionary rating changes have limited power in predicting future loan performance, indicating that the smoothing of credit ratings is only partially driven by information about creditworthiness. Instead, in line with the implicit contract view of credit relationships loan officers are more likely to smooth ratings when rating shocks have stronger implications for interest rates.

Suggested Citation

  • Martin Brown & Matthias Schaller & Simone Westerfeld & Markus Heusler, 2012. "Information or Insurance? On the Role of Loan Officer Discretion in Credit Assessment," Mo.Fi.R. Working Papers 67, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
  • Handle: RePEc:anc:wmofir:67
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    References listed on IDEAS

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    Cited by:

    1. Moro, Andrea & Maresch, Daniela & Fink, Matthias & Ferrando, Annalisa & Piga, Claudio, 2020. "Spillover effects of government initiatives fostering entrepreneurship on the access to bank credit for entrepreneurial firms in Europe," Journal of Corporate Finance, Elsevier, vol. 62(C).
    2. Agarwal, Sumit & Ben-David, Itzhak, 2018. "Loan prospecting and the loss of soft information," Journal of Financial Economics, Elsevier, vol. 129(3), pages 608-628.
    3. Paola Morales‐Acevedo & Steven Ongena, 2020. "Fear, Anger, And Credit. On Bank Robberies And Loan Conditions," Economic Inquiry, Western Economic Association International, vol. 58(2), pages 921-952, April.
    4. Masazumi Hattori & Kohei Shintani & Hirofumi Uchida, 2015. "The Repository of Soft Information within Bank Organizations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(4), pages 737-770, June.
    5. Janis Skrastins & Vikrant Vig, 2019. "How Organizational Hierarchy Affects Information Production," The Review of Financial Studies, Society for Financial Studies, vol. 32(2), pages 564-604.
    6. Stefano Filomeni & Udichibarna Bose & Anastasios Megaritis & Athanasios Triantafyllou, 2024. "Can market information outperform hard and soft information in predicting corporate defaults?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3567-3592, July.
    7. Stefano Filomeni & Gregory F. Udell & Alberto Zazzaro, 2016. "Hardening Soft Information: How Far Has Technology Taken Us?," Mo.Fi.R. Working Papers 121, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    8. Giorgio Albareto & Roberto Felici & Enrico Sette, 2016. "Does credit scoring improve the selection of borrowers and credit quality?," Temi di discussione (Economic working papers) 1090, Bank of Italy, Economic Research and International Relations Area.
    9. Rogger, Daniel & Somani, Ravi, 2023. "Hierarchy and Information," Journal of Public Economics, Elsevier, vol. 219(C).
    10. Gropp, Reint & Guettler, Andre, 2018. "Hidden gems and borrowers with dirty little secrets: Investment in soft information, borrower self-selection and competition," Journal of Banking & Finance, Elsevier, vol. 87(C), pages 26-39.
    11. Alessandro Bitetto & Stefano Filomeni & Michele Modina, 2021. "Understanding corporate default using Random Forest: The role of accounting and market information," DEM Working Papers Series 205, University of Pavia, Department of Economics and Management.
    12. Mosk, T.C., 2014. "Essays on banking," Other publications TiSEM d424ec24-1bfd-4be0-b19a-3, Tilburg University, School of Economics and Management.
    13. José María Liberti & Mitchell A. Petersen, 2018. "Information: Hard and Soft," NBER Working Papers 25075, National Bureau of Economic Research, Inc.
    14. José María Liberti & Mitchell A Petersen, 2019. "Information: Hard and Soft," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 8(1), pages 1-41.

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    More about this item

    Keywords

    Asymmetric information; Credit rating; Implicit contracts; Relationship banking;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

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