Ceci, M. orcid.org/0000-0003-3800-0906, Sannier, N. orcid.org/0000-0002-4449-5792, Abualhaija, S. orcid.org/0000-0001-6095-447X et al. (3 more authors) (2024) Toward automated compliance checking of fund activities using runtime verification techniques. In: FinanSE '24: Proceedings of the 1st IEEE/ACM Workshop on Software Engineering Challenges in Financial Firms. FinanSE '24: 1st IEEE/ACM Workshop on Software Engineering Challenges in Financial Firms, 16 Apr 2024, Lisbon, Portugal. Association for Computing Machinery , New York, United States , pp. 19-20. ISBN 9798400705687
Abstract
Fund activities such as subscriptions or redemption of shares to issuers, fee management, and acquisition or sale of holdings may affect the fund's compliance to requirements of different sources (legal, regulatory but also self-imposed requirements) with potentially huge impact such as hefty fines. One pressing challenge for fund managers and regulators is to target live monitoring of such activities in order to evaluate compliance as soon as possible and in a continuous way. Setting the rules for automatic monitoring and checking the compliance of fund activities is difficult due to the complexity and heterogeneity of the applicable requirements and the observability of data. In this position paper, we introduce our vision toward runtime monitoring of fund activities. Specifically, we aim at extracting monitoring rules from legislation and fund documentation and at providing automated support for enabling the runtime verification of fund activities.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Except as otherwise noted, this author-accepted version of a paper published in FinanSE '24: Proceedings of the 1st IEEE/ACM Workshop on Software Engineering Challenges in Financial Firms is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | FinTech; fund monitoring; runtime verification; information extraction |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 25 Nov 2024 12:13 |
Last Modified: | 25 Nov 2024 12:13 |
Status: | Published |
Publisher: | Association for Computing Machinery |
Refereed: | Yes |
Identification Number: | 10.1145/3643665.3648045 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:220045 |