Can Machine Learning, as a RegTech Compliance Tool, lighten the Regulatory Burden for Charitable Organisations in the United Kingdom?

Singh, C., Zhao, L., Lin, W and Ye, Z 2022. Can Machine Learning, as a RegTech Compliance Tool, lighten the Regulatory Burden for Charitable Organisations in the United Kingdom? Journal of Financial Crime. 29 (1), pp. 45-61. https://doi.org/10.1108/JFC-06-2021-0131

TitleCan Machine Learning, as a RegTech Compliance Tool, lighten the Regulatory Burden for Charitable Organisations in the United Kingdom?
TypeJournal article
AuthorsSingh, C., Zhao, L., Lin, W and Ye, Z
Abstract

Purpose: The purpose of this article is to explore the extent to which machine learning can be used as solution to lighten the compliance and regulatory burden on charitable organisations in the United Kingdom.

Design/methodology/approach: The subject is approached through the analysis of data, literature, and domestic and international regulation. The first part of the article summarises the extent of current regulatory obligations faced by charities, these are then, in the second part, set against the potential technological solutions provided by machine learning as at July 2021.

Findings: It is suggested that charities can utilise machine learning as a smart technological solution to ease the regulatory burden they face in a growing and impactful sector.

Originality: The work is original because it is the first to specifically explore how machine learning as a technological advance can assist charities in meeting the regulatory compliance challenge.

KeywordsMachine Learning, RegTech, Artificial Intelligence, Unsupervised Learning, Financial Crime and English Law
JournalJournal of Financial Crime
Journal citation29 (1), pp. 45-61
ISSN1359-0790
Year2022
PublisherEmerald Publishing Limited
Accepted author manuscript
License
CC BY-NC-ND 4.0
File Access Level
Open (open metadata and files)
Digital Object Identifier (DOI)https://doi.org/10.1108/JFC-06-2021-0131
Web address (URL)https://www.emerald.com/insight/content/doi/10.1108/JFC-06-2021-0131/full/html
Publication dates
Published online06 Aug 2021
Published in print10 Jan 2022

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