IDEAS home Printed from https://ideas.repec.org/b/bis/bisifb/57.html
   My bibliography  Save this book

Machine learning in central banking

Author

Listed:
  • Irving Fisher Committee

Abstract

No abstract is available for this item.

Individual chapters are listed in the "Chapters" tab

Suggested Citation

  • Irving Fisher Committee, 2022. "Machine learning in central banking," IFC Bulletins, Bank for International Settlements, number 57, July.
  • Handle: RePEc:bis:bisifb:57
    as

    Download full text from publisher

    File URL: http://www.bis.org/ifc/publ/ifcb57.pdf
    File Function: Full PDF document
    Download Restriction: no

    File URL: http://www.bis.org/ifc/publ/ifcb57.htm
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Leonard Sabetti & Ronald Heijmans, 2020. "Shallow or deep? Detecting anomalous flows in the Canadian Automated Clearing and Settlement System using an autoencoder," Working Papers 681, DNB.
    2. Klee, Elizabeth, 2010. "Operational outages and aggregate uncertainty in the federal funds market," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2386-2402, October.
    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. Luis Gerardo Gage & Raúl Morales-Resendiz & John Arroyo & Jeniffer Rubio & Paolo Barucca, 2022. "Classifying payment patterns with artificial neural networks: an autoencoder approach," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Machine learning in central banking, volume 57, Bank for International Settlements.
    2. Paulick, Jan & Berndsen, Ron & Diehl, Martin & Heijmans, Ronald, 2021. "No more Tears without Tiers? The Impact of Indirect Settlement on liquidity use in TARGET2," Other publications TiSEM 57477131-2199-46bf-a2f1-5, Tilburg University, School of Economics and Management.
    3. Sabetti, Leonard & Heijmans, Ronald, 2021. "Shallow or deep? Training an autoencoder to detect anomalous flows in a retail payment system," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 2(2).
    4. León, Carlos & Barucca, Paolo & Acero, Oscar & Gage, Gerardo & Ortega, Fabio, 2020. "Pattern recognition of financial institutions’ payment behavior," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    5. 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.
    6. Nellen, Thomas, 2019. "Intraday liquidity facilities, late settlement fee and coordination," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 124-131.
    7. Foote, Elizabeth, 2014. "Information asymmetries and spillover risk in settlement systems," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 179-190.
    8. Bech, Morten & Monnet, Cyril, 2016. "A search-based model of the interbank money market and monetary policy implementation," Journal of Economic Theory, Elsevier, vol. 164(C), pages 32-67.
    9. Neville Arjani & Ronald Heijmans, 2020. "Is there anybody out there? Detecting operational outages from LVTS transaction data," Working Papers 683, DNB.
    10. Kopchak, Seth J., 2011. "The liquidity effect for open market operations," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3292-3299.

    Book Chapters

    The following chapters of this book are listed in IDEAS

    More about this item

    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:bisifb:57. 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: Christian Beslmeisl (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.