IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-032-00118-4_5.html
   My bibliography  Save this book chapter

Using Artificial Intelligence to Combat Fraud: Asian Experience, Russian Prospects

Author

Listed:
  • Anastasia Babanskaya

    (Financial University under the Government of the Russian Federation)

  • Daria Ermoleva

    (Financial University under the Government of the Russian Federation)

  • Nadezhda Efimenko

    (Financial University under the Government of the Russian Federation)

  • Ivan Kotlyarov

    (Financial University under the Government of the Russian Federation)

  • Denis Koleznev

    (Financial University under the Government of the Russian Federation)

Abstract

The use of artificial intelligence today is more widespread than ever. The areas and opportunities for using AI to combat fraud at all stages are expanding every year. Therefore, it is very important to use the best practices of other countries, especially those following the path of advanced development. The purpose of the article is to study the experience of the UAE and India to pinpoint best practices in using AI and combating corporate fraud. The object of the study is AI-based technological solutions to identify anomalies in financial data sets and prevent fraud. The work uses qualitative methods of analyzing scientific literature, state development programs and national projects, case situations, methods of comparative statistical analysis and analogies. Based on the case studies, it was established that the priority areas for developing AI solutions are the banking sector, government agencies, cybersecurity and transactions of organizations, and interaction with partners. The next stage involved identifying areas for combating corporate fraud for individual AI subtechnologies. As a result, the study comes up with proposals on using individual AI subtechnologies to counter fraud.

Suggested Citation

  • Anastasia Babanskaya & Daria Ermoleva & Nadezhda Efimenko & Ivan Kotlyarov & Denis Koleznev, 2025. "Using Artificial Intelligence to Combat Fraud: Asian Experience, Russian Prospects," Lecture Notes in Information Systems and Organization,, Springer.
  • Handle: RePEc:spr:lnichp:978-3-032-00118-4_5
    DOI: 10.1007/978-3-032-00118-4_5
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:lnichp:978-3-032-00118-4_5. 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.