IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-3-031-46177-4_26.html
   My bibliography  Save this book chapter

Effects of Artificial Intelligence on Money Laundering in Southern Africa

In: Towards Digitally Transforming Accounting and Business Processes

Author

Listed:
  • Mufaro Dzingirai

    (Midlands State University)

Abstract

It is interesting to observe that artificial intelligence is gaining popularity in both developing and developed countries as it attracted the interest of accounting, business, and management professionals. This necessitates the need to scrutinise the interaction between artificial intelligence and money laundering. There is an ongoing debate concerning the justifications of artificial intelligence in dealing with money laundering. In this regard, the Southern Africa region is no exception to money laundering just like any other region. As such, the application of artificial intelligence appears to be a rational strategy to curb financial leakages in the finance sector. Although there is an increase in the adoption of artificial intelligence, scanty is known concerning the association between the application of artificial intelligence and money laundering, especially in the Southern Africa region. In this respect, this research aims to provide the effects of artificial intelligence on money laundering in the Southern African region. The study adopted the structured literature review methodology and then six positive effects were observed. These are detecting money laundering activities, enhancing legal compliance, augmenting customer behavioural analytics, detecting money laundering networks, robust financial crime risk computation, and informing evidence-based policy formulation. However, the negative effects are in the form of infringing customer privacy rights, and poor data governance. Despite the existence of few negative effects, it is concluded that artificial intelligence helps to combat money laundering in the Southern African region. As such, it is suggested that financial institutions should up-skill their personnel and up-scale their business intelligence projects.

Suggested Citation

  • Mufaro Dzingirai, 2024. "Effects of Artificial Intelligence on Money Laundering in Southern Africa," Springer Proceedings in Business and Economics, in: Tankiso Moloi & Babu George (ed.), Towards Digitally Transforming Accounting and Business Processes, pages 483-500, Springer.
  • Handle: RePEc:spr:prbchp:978-3-031-46177-4_26
    DOI: 10.1007/978-3-031-46177-4_26
    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 search for a similarly titled item that would be available.

    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:prbchp:978-3-031-46177-4_26. 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.