IDEAS home Printed from https://ideas.repec.org/b/bis/bisbps/145.html

Generative artificial intelligence and cyber security in central banking

Author

Listed:
  • Iñaki Aldasoro
  • Sebastian Doerr
  • Leonardo Gambacorta
  • Sukhvir Notra
  • Tommaso Oliviero
  • David Whyte

Abstract

Generative artificial intelligence (gen AI) introduces novel opportunities to strengthen central banks' cyber security but also presents new risks. We use data from a unique survey among cyber security experts at major central banks to shed light on these issues. Responses reveal that most central banks have already adopted or plan to adopt gen AI tools in the context of cyber security, as perceived benefits outweigh risks. Experts foresee that AI tools will improve cyber threat detection and reduce response time to cyber attacks. Yet gen AI also increases the risks of social engineering attacks and unauthorised data disclosure. To mitigate these risks and harness the benefits of gen AI, central banks anticipate a need for substantial investments in human capital, especially in staff with expertise in both cyber security and AI programming. Finally, while respondents expect gen AI to automate various tasks, they also expect it to support human experts in other roles, such as oversight of AI models.

Suggested Citation

  • Iñaki Aldasoro & Sebastian Doerr & Leonardo Gambacorta & Sukhvir Notra & Tommaso Oliviero & David Whyte, 2024. "Generative artificial intelligence and cyber security in central banking," BIS Papers, Bank for International Settlements, number 145, February.
  • Handle: RePEc:bis:bisbps:145
    as

    Download full text from publisher

    File URL: http://www.bis.org/publ/bppdf/bispap145.pdf
    File Function: Full PDF document
    Download Restriction: no

    File URL: http://www.bis.org/publ/bppdf/bispap145.htm
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Iñaki Aldasoro & Leonardo Gambacorta & Paolo Giudici & Thomas Leach, 2023. "Operational and Cyber Risks in the Financial Sector," International Journal of Central Banking, International Journal of Central Banking, vol. 19(5), pages 340-402, December.
    2. Doerr, Sebastian & Gambacorta, Leonardo & Leach, Thomas & Legros, Bertrand & Whyte, David, 2022. "Cyber risk in central banking," CEPR Discussion Papers 17660, C.E.P.R. Discussion Papers.
    3. Aldasoro, Iñaki & Gambacorta, Leonardo & Giudici, Paolo & Leach, Thomas, 2022. "The drivers of cyber risk," Journal of Financial Stability, Elsevier, vol. 60(C).
    4. Edward Felten & Manav Raj & Robert Seamans, 2021. "Occupational, industry, and geographic exposure to artificial intelligence: A novel dataset and its potential uses," Strategic Management Journal, Wiley Blackwell, vol. 42(12), pages 2195-2217, December.
    Full references (including those not matched with items on IDEAS)

    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. Ajjima Jiravichai & Ruth Banomyong, 2022. "A Proposed Methodology for Literature Review on Operational Risk Management in Banks," Risks, MDPI, vol. 10(5), pages 1-18, May.
    2. Uddin, Md Hamid & Mollah, Sabur & Islam, Nazrul & Ali, Md Hakim, 2023. "Does digital transformation matter for operational risk exposure?," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    3. Md. Hamid Uddin & Md. Hakim Ali & Mohammad Kabir Hassan, 2020. "Cybersecurity hazards and financial system vulnerability: a synthesis of literature," Risk Management, Palgrave Macmillan, vol. 22(4), pages 239-309, December.
    4. Kwangmin Jung & Chanjin Kim & Jiyeon Yun, 2025. "The effect of corporate risk management on cyber risk mitigation: Evidence from the insurance industry," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 50(2), pages 259-301, April.
    5. Doerr, Sebastian & Gambacorta, Leonardo & Leach, Thomas & Legros, Bertrand & Whyte, David, 2022. "Cyber risk in central banking," CEPR Discussion Papers 17660, C.E.P.R. Discussion Papers.
    6. Eisenbach, Thomas M. & Kovner, Anna & Lee, Michael Junho, 2022. "Cyber risk and the U.S. financial system: A pre-mortem analysis," Journal of Financial Economics, Elsevier, vol. 145(3), pages 802-826.
    7. Iñaki Aldasoro & Leonardo Gambacorta & Paolo Giudici & Thomas Leach, 2023. "Operational and Cyber Risks in the Financial Sector," International Journal of Central Banking, International Journal of Central Banking, vol. 19(5), pages 340-402, December.
    8. Joshua S. Gans, 2023. "Artificial intelligence adoption in a competitive market," Economica, London School of Economics and Political Science, vol. 90(358), pages 690-705, April.
    9. Egana-delSol, Pablo & Vargas-Faulbaum, Luis, 2025. "Artificial Intelligence and the Future of Work: Evidence and Policy Guidelines for Developing Economies," IZA Policy Papers 216, Institute of Labor Economics (IZA).
    10. Zara Contractor & Germ'an Reyes, 2025. "Generative AI in Higher Education: Evidence from an Elite College," Papers 2508.00717, arXiv.org.
    11. Ren, Yi-Shuai & Ma, Chaoqun & Wang, Yiran, 2024. "A new financial regulatory framework for digital finance: Inspired by CBDC," Global Finance Journal, Elsevier, vol. 62(C).
    12. Christos Makridis & Christos A. Makridis, 2025. "The Labor Market Effect of Generative Artificial Intelligence on Artists," CESifo Working Paper Series 12368, CESifo.
    13. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    14. Federico Riccio & Jacopo Staccioli & Maria Enrica Virgillito, 2025. "European regional employment and exposure to labour-saving technical change: results from a direct text similarity measure," LEM Papers Series 2025/19, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    15. Malavasi, Matteo & Peters, Gareth W. & Shevchenko, Pavel V. & Trück, Stefan & Jang, Jiwook & Sofronov, Georgy, 2022. "Cyber risk frequency, severity and insurance viability," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 90-114.
    16. Enrico Maria Fenoaltea & Dario Mazzilli & Aurelio Patelli & Angelica Sbardella & Andrea Tacchella & Andrea Zaccaria & Marco Trombetti & Luciano Pietronero, 2024. "Follow the money: a startup-based measure of AI exposure across occupations, industries and regions," Papers 2412.04924, arXiv.org, revised Dec 2024.
    17. Cattaneo, Maria A. & Gschwendt, Christian & Wolter, Stefan C., 2025. "How scary is the risk of automation? Evidence from a large-scale survey experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 235(C).
    18. Benedetta Montanaro & Annalisa Croce & Elisa Ughetto, 2024. "Venture capital investments in artificial intelligence," Journal of Evolutionary Economics, Springer, vol. 34(1), pages 1-28, January.
    19. Matteo Malavasi & Gareth W. Peters & Pavel V. Shevchenko & Stefan Truck & Jiwook Jang & Georgy Sofronov, 2021. "Cyber Risk Frequency, Severity and Insurance Viability," Papers 2111.03366, arXiv.org, revised Mar 2022.
    20. Cameron D. Miller & Richard D. Wang, 2024. "Product digitization and differentiation strategy change: Evidence from the book publishing industry," Strategic Management Journal, Wiley Blackwell, vol. 45(7), pages 1241-1272, July.

    More about this item

    JEL classification:

    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • K23 - Law and Economics - - Regulation and Business Law - - - Regulated Industries and Administrative Law

    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:bis:bisbps:145. 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: Martin Fessler (email available below). General contact details of provider: https://edirc.repec.org/data/bisssch.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.