IDEAS home Printed from https://ideas.repec.org/a/anr/refeco/v17y2025p363-393.html

Generative AI and Finance

Author

Listed:
  • Andrea L. Eisfeldt

    (Anderson School of Management, University of California, Los Angeles, California, USA)

  • Gregor Schubert

    (Anderson School of Management, University of California, Los Angeles, California, USA)

Abstract

Since ChatGPT's release in 2022, demand for artificial intelligence (AI)–related skills in finance has grown rapidly, as generative AI drives significant technological changes in both the financial research field and the broader economy. We show that financial occupations are highly exposed to the productivity effects of generative AI, review the literature on the impact of ChatGPT on firm value, and provide directions for future research investigating the impact of this major technology shock. Generative AI also holds great potential as a tool for finance researchers and practitioners: We review and describe innovations in research methods linked to improvements in AI tools, along with their applications. We offer a practical introduction to available tools and advice for researchers in academia and industry interested in using these tools.

Suggested Citation

  • Andrea L. Eisfeldt & Gregor Schubert, 2025. "Generative AI and Finance," Annual Review of Financial Economics, Annual Reviews, vol. 17(1), pages 363-393, November.
  • Handle: RePEc:anr:refeco:v:17:y:2025:p:363-393
    DOI: 10.1146/annurev-financial-112923-020503
    as

    Download full text from publisher

    File URL: https://doi.org/10.1146/annurev-financial-112923-020503
    Download Restriction: Full text downloads are only available to subscribers. Visit the abstract page for more information.

    File URL: https://libkey.io/10.1146/annurev-financial-112923-020503?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • G00 - Financial Economics - - General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    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:anr:refeco:v:17:y:2025:p:363-393. 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: http://www.annualreviews.org (email available below). General contact details of provider: http://www.annualreviews.org .

    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.