Securities market automation from standards to self-learning machines: Current state and future perspectives

Jonathan Ehrenfeld
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Jonathan Ehrenfeld: Strategy Director, SWIFT, Belgium

Journal of Securities Operations & Custody, 2017, vol. 9, issue 3, 245-251

Abstract: Over the last two decades, key aspects of the financial industry have been automated to a substantial degree. While most progress in automation has come from traditional technologies, recent advances in machine learning, artificial intelligence and robotics are likely to accelerate the pace. In such a context, Distributed Ledger Technologies, Robo-Advisors and cognitive tools are creating a foundation for solving major problems faced by the industry. This paper provides an overview of the capabilities and limitations of these technologies and the challenges that await market participants who want to embrace and implement them. It draws attention to the importance of collaboration, governance, standards and market practice harmonisation in order to successfully deploy these technologies in a multi-party, globalised network environment.

Keywords: securities; technology; artificial intelligence; distributed ledger technologies (DLTs); robotics; cognitive computing; standards (search for similar items in EconPapers)
JEL-codes: E5 G2 K22 (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:aza:jsoc00:y:2017:v:9:i:3:p:245-251

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