|Title||Can Machine Learning, as a RegTech Compliance Tool, lighten the Regulatory Burden for Charitable Organisations in the United Kingdom?|
|Authors||Singh, C., Zhao, L., Lin, W and Ye, Z|
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.
|Keywords||Machine Learning, RegTech, Artificial Intelligence, Unsupervised Learning, Financial Crime and English Law|
|Journal||Journal of Financial Crime|
|Accepted author manuscript|
Can Machine Learning, as a RegTech Compliance Tool, lighten the Regulatory Burden for Charitable Organisations in the United Kingdom?.pdf
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|
|Published online||06 Aug 2021|