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Blockchain Application to Financial Market Clearing and Settlement Systems

Author

Listed:
  • Nipun Agarwal

    (School of Business, University of Notre Dame, Sydney 2007, Australia)

  • Pornpit Wongthongtham

    (School of Business, University of Notre Dame, Sydney 2007, Australia)

  • Neerajkumari Khairwal

    (L1X Foundation, c/o Sielva Management SA, Gubelstrasse 11, CH-6300 Zug, Switzerland)

  • Kevin Coutinho

    (L1X Foundation, c/o Sielva Management SA, Gubelstrasse 11, CH-6300 Zug, Switzerland)

Abstract

Blockchain technology has emerged as a transformative force in the financial industry, offering the potential to streamline and enhance financial markets’ clearing and settlement processes. This paper explores the application of blockchain technology in these critical areas. We examine traditional clearing and settlement procedures, the challenges they pose, and how blockchain can address these issues. Through case studies and technical insights, we illustrate the benefits and limitations of implementing blockchain solutions. This paper utilizes the PRISMA method to survey papers related to blockchain-based clearing and settlement systems, while using Science Direct to identify papers that have been published in this area. These papers were reviewed to identify themes that relate to extending blockchain development for clearing and settlement system in financial markets. As a result, this paper also shows how the Layer One X (L1X) blockchain can be applied to develop financial markets clearing and settlement systems.

Suggested Citation

  • Nipun Agarwal & Pornpit Wongthongtham & Neerajkumari Khairwal & Kevin Coutinho, 2023. "Blockchain Application to Financial Market Clearing and Settlement Systems," JRFM, MDPI, vol. 16(10), pages 1-19, October.
    • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:10:p:452-:d:1263933
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    References listed on IDEAS

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    Cited by:

    1. Mahima Habil & Saransh Kumar Srivastav & Pooja Thakur, 2024. "Mapping the landscape of blockchain technology: a bibliometric analysis," Journal of Computational Social Science, Springer, vol. 7(2), pages 1533-1553, October.

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