IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/19051.html
   My bibliography  Save this paper

Loan officer Incentives and the Limits of Hard Information

Author

Listed:
  • Tobias Berg
  • Manju Puri
  • Jorg Rocholl

Abstract

Poor loan quality is often attributed to loan officers exercising poor judgment. A potential solution is to base loans on hard information alone. However, we find other consequences of bypassing discretion stemming from loan officer incentives and limits of hard information verifiability. Using unique data where loans are based on hard information, and loan officers are volume-incentivized, we find loan officers increasingly use multiple trials to move loans over the cut-off, both in a regression-discontinuity design and when the cut-off changes. Additional trials positively predict default suggesting strategic manipulation of information even when loans are based on hard information alone.

Suggested Citation

  • Tobias Berg & Manju Puri & Jorg Rocholl, 2013. "Loan officer Incentives and the Limits of Hard Information," NBER Working Papers 19051, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19051
    Note: CF
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w19051.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shawn Cole & Martin Kanz & Leora Klapper, 2015. "Incentivizing Calculated Risk-Taking: Evidence from an Experiment with Commercial Bank Loan Officers," Journal of Finance, American Finance Association, vol. 70(2), pages 537-575, April.
    2. Berger, Allen N. & Miller, Nathan H. & Petersen, Mitchell A. & Rajan, Raghuram G. & Stein, Jeremy C., 2005. "Does function follow organizational form? Evidence from the lending practices of large and small banks," Journal of Financial Economics, Elsevier, vol. 76(2), pages 237-269, May.
    3. Puri, Manju & Rocholl, Jörg & Steffen, Sascha, 2011. "Global retail lending in the aftermath of the US financial crisis: Distinguishing between supply and demand effects," Journal of Financial Economics, Elsevier, vol. 100(3), pages 556-578, June.
    4. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
    5. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    6. Jose M. Liberti & Atif R. Mian, 2009. "Estimating the Effect of Hierarchies on Information Use," The Review of Financial Studies, Society for Financial Studies, vol. 22(10), pages 4057-4090, October.
    7. Andrew Hertzberg & Jose Maria Liberti & Daniel Paravisini, 2010. "Information and Incentives Inside the Firm: Evidence from Loan Officer Rotation," Journal of Finance, American Finance Association, vol. 65(3), pages 795-828, June.
    8. Gary Chamberlain, 1980. "Analysis of Covariance with Qualitative Data," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 225-238.
    9. Jeremy C. Stein, 2002. "Information Production and Capital Allocation: Decentralized versus Hierarchical Firms," Journal of Finance, American Finance Association, vol. 57(5), pages 1891-1921, October.
    10. Ben-David, Itzhak & Agarwal, Sumit, 2012. "Do Loan Officers' Incentives Lead to Lax Lending Standards?," Working Paper Series 2012-07, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    11. Udell, Gregory F., 1989. "Loan quality, commercial loan review and loan officer contracting," Journal of Banking & Finance, Elsevier, vol. 13(3), pages 367-382, July.
    12. Benjamin J. Keys & Tanmoy Mukherjee & Amit Seru & Vikrant Vig, 2010. "Did Securitization Lead to Lax Screening? Evidence from Subprime Loans," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(1), pages 307-362.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Andrea Bellucci & Alexander Borisov & Alberto Zazzaro, 2016. "Bank Organization and Loan Contracting in Small Business Financing," Mo.Fi.R. Working Papers 118, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    2. Jere R. Francis & Wei Wang, 2021. "Common Auditors and Private Bank Loans," Contemporary Accounting Research, John Wiley & Sons, vol. 38(1), pages 793-832, March.
    3. Stefano Filomeni & Gregory F. Udell & Alberto Zazzaro, 2016. "Hardening Soft Information: How Far Has Technology Taken Us?," CSEF Working Papers 455, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    4. Luojia Hu & Xing Huang & Andrei Simonov, 2020. "Credit Score Doctors," Working Paper Series WP 2020-07, Federal Reserve Bank of Chicago.
    5. Vojtech, Cindy M. & Kay, Benjamin S. & Driscoll, John C., 2020. "The real consequences of bank mortgage lending standards," Journal of Financial Intermediation, Elsevier, vol. 44(C).
    6. Kilian R. Dinkelaker & Andreas-Walter Mattig & Stefan Morkoetter, 2019. "A Closer Look at Credt Rating Processes: Uncovering the Impact of Analyst Rotation," Working Papers on Finance 1911, University of St. Gallen, School of Finance.
    7. Behr, Patrick & Drexler, Alejandro & Gropp, Reint & Guettler, Andre, 2020. "Financial Incentives and Loan Officer Behavior: Multitasking and Allocation of Effort under an Incomplete Contract," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(4), pages 1243-1267, June.
    8. Franz Flögel, 2018. "Distance and Modern Banks’ Lending to SMEs: Ethnographic Insights from a Comparison of Regional and Large Banks in Germany," Journal of Economic Geography, Oxford University Press, vol. 18(1), pages 35-57.
    9. 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.
    10. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
    11. Franz Flögel & Marius Beckamp, 2020. "Will FinTech make regional banks superfluous for small firm finance? Observations from soft information‐based lending in Germany," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 49(2), July.
    12. 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.
    13. Alejandro Drexler & Antoinette Schoar, 2014. "Do Relationships Matter? Evidence from Loan Officer Turnover," Management Science, INFORMS, vol. 60(11), pages 2722-2736, November.
    14. Steven Ongena, 2014. "Discussion of Presbitero, Udell, and Zazzaro," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(s1), pages 87-91, February.
    15. Porzio, Claudio & Sampagnaro, Gabriele & Verdoliva, Vincenzo, 2020. "Lost in Translation: The determinants and the effect of soft information dispersion in bank lending," Global Finance Journal, Elsevier, vol. 43(C).
    16. Ha Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," Working Papers hal-04141336, HAL.
    17. Bushman, Robert & Gao, Janet & Martin, Xiumin & Pacelli, Joseph, 2021. "The influence of loan officers on loan contract design and performance," Journal of Accounting and Economics, Elsevier, vol. 71(2).
    18. Mosk, T.C., 2014. "Essays on banking," Other publications TiSEM d424ec24-1bfd-4be0-b19a-3, Tilburg University, School of Economics and Management.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sauro Mocetti & Marcello Pagnini & Enrico Sette, 2017. "Information Technology and Banking Organization," Journal of Financial Services Research, Springer;Western Finance Association, vol. 51(3), pages 313-338, June.
    2. Tantri, Prasanna, 2021. "Identifying ever-greening: Evidence using loan-level data," Journal of Banking & Finance, Elsevier, vol. 122(C).
    3. Vojtech, Cindy M. & Kay, Benjamin S. & Driscoll, John C., 2020. "The real consequences of bank mortgage lending standards," Journal of Financial Intermediation, Elsevier, vol. 44(C).
    4. Andrea F. Presbitero & Gregory F. Udell & Alberto Zazzaro, 2014. "The Home Bias and the Credit Crunch: A Regional Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(s1), pages 53-85, February.
    5. Shawn Cole & Martin Kanz & Leora Klapper, 2015. "Incentivizing Calculated Risk-Taking: Evidence from an Experiment with Commercial Bank Loan Officers," Journal of Finance, American Finance Association, vol. 70(2), pages 537-575, April.
    6. Uchida, Hirofumi & Udell, Gregory F. & Yamori, Nobuyoshi, 2012. "Loan officers and relationship lending to SMEs," Journal of Financial Intermediation, Elsevier, vol. 21(1), pages 97-122.
    7. Stefano Filomeni & Gregory F. Udell & Alberto Zazzaro, 2016. "Hardening Soft Information: How Far Has Technology Taken Us?," CSEF Working Papers 455, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    8. Jens Grunert & Lars Norden, 2012. "Bargaining power and information in SME lending," Small Business Economics, Springer, vol. 39(2), pages 401-417, September.
    9. 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.
    10. Michele Benvenuti & Luca Casolaro & Silvia Del Prete & Paolo Emilio Mistrulli, 2017. "The Right to Decide and the Effective Control Over Small Business Lending Decisions: A Look into Loan Officers’ Real Authority," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 46(2), pages 237-268, July.
    11. Bushman, Robert & Gao, Janet & Martin, Xiumin & Pacelli, Joseph, 2021. "The influence of loan officers on loan contract design and performance," Journal of Accounting and Economics, Elsevier, vol. 71(2).
    12. 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.
    13. José María Liberti & Mitchell A. Petersen, 2018. "Information: Hard and Soft," NBER Working Papers 25075, National Bureau of Economic Research, Inc.
    14. Marcello Pagnini & Silvia Del Prete & Paola Rossi & Valerio Vacca, 2013. "Lending Organization and Credit Supply During the Crisis," ERSA conference papers ersa13p673, European Regional Science Association.
    15. Luca Papi & Emma Sarno & Alberto Zazzaro, 2017. "The geographical network of bank organizations: issues and evidence for Italy," Chapters, in: Ron Martin & Jane Pollard (ed.), Handbook on the Geographies of Money and Finance, chapter 8, pages 156-196, Edward Elgar Publishing.
    16. Pietro Alessandrini & Andrea F. Presbitero & Alberto Zazzaro, 2009. "Banks, Distances and Firms' Financing Constraints," Review of Finance, European Finance Association, vol. 13(2), pages 261-307.
    17. Campbell, Dennis & Loumioti, Maria & Wittenberg-Moerman, Regina, 2019. "Making sense of soft information: interpretation bias and loan quality," Journal of Accounting and Economics, Elsevier, vol. 68(2).
    18. Mosk, T.C., 2014. "Essays on banking," Other publications TiSEM d424ec24-1bfd-4be0-b19a-3, Tilburg University, School of Economics and Management.
    19. Bertrand, Jérémie & Murro, Pierluigi, 2022. "Firm–bank “odd couples” and trade credit: Evidence from Italian small- and medium-sized enterprises," Economic Modelling, Elsevier, vol. 111(C).
    20. Behr, Patrick & Drexler, Alejandro & Gropp, Reint & Guettler, Andre, 2020. "Financial Incentives and Loan Officer Behavior: Multitasking and Allocation of Effort under an Incomplete Contract," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(4), pages 1243-1267, June.

    More about this item

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G2 - Financial Economics - - Financial Institutions and Services
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G3 - Financial Economics - - Corporate Finance and Governance

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:19051. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.