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Applying artificial intelligence in finance and asset management: A discussion of status quo and the way forward

Author

Listed:
  • Dr. Rahmel, Juergen

    (HSBC Germany)

Abstract

Artificial intelligence (AI) and machine learning (ML) are gaining more and more traction in finance and asset management. But AI/ML is a complex tool that requires specific skills to be created, trained, and interpreted well for a given task. In this paper, we discuss some of the context parameters to be considered in order to apply AI beneficially in financial settings. We explore a matrix of use-cases, following the lifecycle of asset management and structured by the type of underlying AI technology. As AI requires human setup and interpretation, we briefly review the role of us “humans-in-the-loop” of AI implementations. Finally, the emerging field of asset tokenization promises to disrupt the conventional markets and market practices, opening up for a new field of AI applications to tackle the new way of trading and servicing securities. The AI game is on in asset management. Not to play is not an option.

Suggested Citation

  • Dr. Rahmel, Juergen, 2020. "Applying artificial intelligence in finance and asset management: A discussion of status quo and the way forward," Journal of Financial Transformation, Capco Institute, vol. 51, pages 67-74.
  • Handle: RePEc:ris:jofitr:1647
    as

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    More about this item

    Keywords

    Artificial Intelligence; Risk; Risk Mining; Asset Tokenization; Explainability;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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