Purpose Artificial intelligence (AI), machine learning (ML) and deep learning (DL) are having a major impact on banking (FinTech), health (HealthTech), law (RegTech) and other sectors such as charitable fundraising (CharityTech). The pace of technological innovation and the ability of AI systems to think like human beings (simulate human intelligence), perform tasks independently, develop intelligence based on its own experiences and process layers of information to learn ever-complex representations of data (ML/DL) means that improvements in the rates at which this technology can undertake complex, technical and time-consuming tasks, identify people, objects, voices, patterns, etc., screen for ‘problems’ earlier, and provide solutions, provide astounding benefit in economic, political and social terms. The purpose of this paper is to explore advents in AI, ML and DL in the context of the regulatory compliance challenge faced by financial institutions in the United Kingdom (UK).
Design/methodology/approach The subject is explored through the analysis of data and domestic and international published literature. The first part of the paper summarises the context of current regulatory issues, the advents in deep learning, how financial institutions are currently using AI, and how AI could provide further technological solutions to regulatory compliance as of February 2023.
Findings It is suggested that UK financial institutions can further utilise AI, ML and DL as part of an armoury of solutions that ease the regulatory burden and achieve high levels of compliance success.
Originality/value To the best of the author’s knowledge, this is the first study to specifically explore how AI, ML and DL can continue to assist UK financial institutions in meeting the regulatory compliance challenge and the opportunities provided for financial institutions by the metaverse.
Artificial intelligence (AI), machine learning (ML) and deep learning (DL) are changing the way in which organisations work. The rate of technological innovation and the ability of AI systems to think like human-beings (simulate human intelligence), perform tasks independently, develop intelligence based on its own experiences and process layers of information to learn ever-complex representations of data (ML/DL) means that improvements in the rates at which this technology can undertake complex, technical, tedious and time-consuming tasks, identify people, objects, voices, patterns, etc., screen for “problems” earlier, and provide solutions, provide astounding benefit in economic, political and social terms. Thus, AI, ML and DL have become buzzwords or colloquialisms that are often used synonymously, albeit all three mean different things, the potential of which is now engrained intimately into the fabric of technology systems as governments, organisations and even regulators seek to benefit from the innovative solutions that they offer.
The purpose of this article is to explore advents in AI, ML and DL in the context of the financial institutions and the regulatory compliance challenge they face in the United Kingdom (UK). This article explores how AI, ML and DL can, as a RegTech tool, assist these organisations in tackling that issue. In so doing, it is investigated what AI, ML and DL can assist with as trustworthy components in the arsenal of financial institutions in assisting regulatory compliance (Singh et al., 2020).
Regulators in the financial services industry are actively engaging with AI, and thus, institutions should also harness the progress made by them, the technology and the RegTech revolution. There is an opportunity to further reduce the occurrence of compliance breaches and crime by expanding the use of DL, where AI can help in the conduct of business. To be fair, the finance sector has grasped many digital and technological transformation initiatives unlike others, such as charities, but a lot more can be done. AI can assist institutions in cutting operational costs, promoting greater levels of regulatory compliance and building stronger relationships based on trust and confidence with stakeholders. Expanding analytical tools and automating processes can assist institutions in reducing risk and successfully fighting financial crime. Finally, the financial services industry needs to further engage with the metaverse so that they can harness the manifold opportunities it offers for new experiences, products and services.