IDEAS home Printed from https://ideas.repec.org/a/kap/jbuset/v198y2025i2d10.1007_s10551-024-05789-7.html
   My bibliography  Save this article

Does Soft Information Mitigate Gender Bias in Corporate Lending?

Author

Listed:
  • Udichibarna Bose

    (University of Essex, Essex Business School, Finance Group)

  • Stefano Filomeni

    (University of Essex, Essex Business School, Finance Group)

  • Elena Tabacco

Abstract

Gender bias in leadership and decision-making is a well-documented and pervasive topic that continues to garner significant attention in academic research and business literature. In this paper, by exploiting a unique proprietary dataset of 550 mid-corporate loan applications managed by a major European bank, we explore how the use of soft information influences lending decisions of female loan officers as compared to their male counterparts. We find that use of soft information reduces information asymmetry which helps female officers in making diligent lending decisions resulting in increased granted credit with a lower default probability. We also investigate gender affinity within the banking organisation and find that female loan approvers are more likely to be supportive of their subordinate female loan officers by approving more credit to the loan applications handled by female loan officers. Finally, we examine the possible mechanisms that can explain these results, and find that female loan officers are able to better collect and use soft information as they cultivate and maintain deeper firm-bank relationships with their clients due to higher threat of losing or being penalized in their jobs for any possible errors. We also rule out any other possible explanations such as differences in workload, work experience, loan officers’ optimism, managerial ability, and screening capabilities between female and male loan officers. Our findings carry important policy implications, reflected in the optimal allocation of capital in the economy and the reduction of gender-related exclusion, which is vital in creating an equitable society and fostering a more ethical and inclusive workplace.

Suggested Citation

  • Udichibarna Bose & Stefano Filomeni & Elena Tabacco, 2025. "Does Soft Information Mitigate Gender Bias in Corporate Lending?," Journal of Business Ethics, Springer, vol. 198(2), pages 437-466, May.
  • Handle: RePEc:kap:jbuset:v:198:y:2025:i:2:d:10.1007_s10551-024-05789-7
    DOI: 10.1007/s10551-024-05789-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10551-024-05789-7
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10551-024-05789-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Soft information; Corporate lending; Female loan officers; Gender bias; Bank organization;
    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
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • M14 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Corporate Culture; Diversity; Social Responsibility

    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:kap:jbuset:v:198:y:2025:i:2:d:10.1007_s10551-024-05789-7. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.