Simplifying Compliance: The Role of AI and RegTech
The Financial Regulation Innovation Lab (FRIL) is dedicated to simplifying compliance through emerging technologies, with Artificial Intelligence (AI) representing the latest evolution in regulatory technology (RegTech). Building on previous research and industry engagement—including workshops, blogs, webinars, and a micro-credential course—this White Paper presents key considerations for the conceptualisation, design, and implementation of AI-driven compliance systems.
We begin by examining the nature of regulatory rules and the compliance process before exploring the complexities that challenge AI deployment. The discussion then shifts to Generative AI (GenAI) as a cutting-edge innovation, analysing its capabilities and relevance to compliance functions.
A focused use case on GenAI in robo-advisory services illustrates AI’s potential in asset management, where conventional AI is already well-established. Finally, we consider the broader organisational implications of AI adoption, emphasising the opportunity to view compliance as an embedded and adaptive function able to evolve and respond to changing stakeholder expectations and regulatory frameworks.
AI and RegTech: Industry Insights on AI in Financial Regulation
Article written by Alessio Azzutti (University of Glasgow), Mark Cummins (University of Strathclyde),
Iain McNeil (University of Glasgow).
Note: Segments of this blog were generated by ChatGPT using notes taken on the day capturing the
presentations and discussions. The authors edited this generated content accordingly.
The integration of Artificial Intelligence (AI) into financial practice and regulatory processes represents a pivotal shift, promising enhanced efficiency, accuracy, and innovation across regulatory compliance and supervision. Our recent discussions explored various facets of AI’s role in financial regulation, revealing a landscape rich with opportunities and challenges. This synthesis (generated by ChatGPT from our discussions with industry partners in our AI & RegTech Workshop on 10 May 2024 and revised by the authors) aims to distill key insights from the discussion across themes, providing an overview of the promises that AI bears on regulatory practices. It will be followed soon by a white paper as part of the White Paper Series published by the Financial Regulation Innovation Lab. This white paper will set out the issues in more detail, linking them to prior research and evolving practice.
Transformation of Regulatory Compliance through AI
AI’s integration into regulatory compliance processes marks a significant evolution in how financial institutions deal with complex regulatory environments. Discussions highlighted AI’s potential to revolutionise compliance by automating and augmenting tasks such as data collection, management and analysis, especially in relation to vast datasets in order to generate actionable insights with unprecedented speed and accuracy. At the same time, the efficacy of AI in compliance hinges on several critical factors. Financial regulations encompass a spectrum of rules ranging from overarching principles to specific quantitative benchmarks and qualitative guidelines.
AI applications must move among these diverse regulatory requirements, which vary in complexity and scope across jurisdictions. Participants underscored the importance of regulatory clarity in fostering AI adoption in compliance (RegTech). Uncertainties about regulatory expectations can stifle innovation in RegTech solutions. Standardisation of data formats, communication protocols, and other AI-related requirements emerged as essential prerequisites to streamline AI integration and enhance compliance efficiency. AI can be integrated into compliance through comprehensive system-wide approaches or targeted solutions for specific regulatory challenges. In addressing the relationship between AI and the various layers of regulation, the roundtable emphasised the need to view compliance as a dynamic process and activity rather than a static framework.
Participants agreed on some crucial aspects related to AI governance. Despite AI’s capabilities, human oversight remains indispensable, for instance, to validate AI outputs, ensure ethical decision-making, and interpret regulatory requirements accurately. Indeed, the discussion highlighted the ongoing need for human experts to manage AI-augmented compliance effectively. Greater standardisation in AI-related technologies and regulatory frameworks are also seen as future catalysts for innovation in the RegTech sector. Standardised practices can enable financial institutions and technology providers to focus on enhancing their AI solutions rather than coping with disparate regulatory landscapes.
Design and Governance of AI-Enabled Compliance Systems
The application of AI, particularly its subfield of Machine Learning (ML) methods, in compliance systems was explored as a transformative force reshaping business strategies and operations within financial institutions. AI systems empower organisations to analyse complex datasets rapidly and derive insights that inform decision-making. Among other things, participants highlighted AI’s role in improving risk management, fraud detection, and overall operational efficiency. However, the design of AI systems in compliance is seen as extending beyond automation to facilitate strategic alignment with business goals and regulatory objectives.
In this context, ensuring effective model governance emerged as a critical priority for organisations deploying AI in regulatory compliance. Robust governance frameworks can help ensure transparency, accountability, and compliance with regulatory standards. The emerging field of Explainable AI (XAI) is deemed critical in financial services to ensure transparency and build trust among stakeholders. Clear explanations of AI processes and decisions enhance user confidence and facilitate regulatory compliance.
Addressing biases—whether in data, models, and their inherent human assumptions—was highlighted as essential to ensure fair outcomes and mitigate risks. Robust governance frameworks include mechanisms for bias detection, mitigation, and continuous monitoring to uphold ethical and legal standards. Discussions emphasised the need for clear policies and procedures to monitor AI models in and along the entire AI lifecycle.
Moreover, the debate between in-house AI development versus third-party vendor solutions highlighted some organisational preferences and challenges. Large financial institutions often opt for in-house development to tailor AI solutions to their specific needs and maintain control over data integrity and security.
Broadly speaking, legal and ethical considerations in AI deployment include data privacy, intellectual property rights, and liability for AI-based decisions. The roundtable discussions emphasised the need for clear regulatory frameworks to address all the complexities embedded in AI governance, which necessitates shared responsibility across stakeholders—developers, users, regulators, and consumers. Clear delineation of roles and responsibilities was deemed crucial by participants to mitigate risks and ensure responsible AI deployment.
The specific exploration of Generative AI in compliance identified its potential in automating routine tasks and enhancing productivity. Despite its benefits, concerns about data privacy, security, and the ethical implications of AI-generated content remain paramount. We heard further calls for human-in-the-loop solutions. Human oversight ensures the credibility and accuracy of Generative AI outputs.
Mutual Reinforcement of RegTech and SupTech
RegTech (regulatory technology) and SupTech (supervisory technology) represent two sides of the same coin, namely the adoption of innovative technology to bring greater effectiveness and efficiency to financial regulation and its enforcement. RegTech tools powered by AI enhance regulatory compliance by improving understanding of regulations, managing business activities, and achieving higher-quality compliance outcomes. However, regulatory fragmentation and differing compliance requirements pose challenges to widespread and trustworthy adoption. In parallel, financial supervisors are researching and gradually adopting AI-based SupTech solutions to enhance their ability to achieve supervisory objectives in an efficient and effective manner. Interoperability between RegTech and SupTech systems is essential for frictionless and secure data exchange between regulators/supervisors and regulated entities in order to improve regulatory oversight. Standardised data formats, communication protocols, and AI-related requirements promote collaboration between financial institutions and regulatory authorities. Greater regulatory clarity and standardisation are seen as catalysts for innovation in the RegTech space. Clear guidelines on regulatory requirements targeting AI applications facilitate technological advancements while ensuring compliance with regulatory standards. Collaboration between public authorities, financial institutions, and technology providers is expected to foster a conducive ecosystem for AI innovation in financial regulation. The roundtable discussions emphasised the importance of collaborative efforts to overcome regulatory challenges and promote technological convergence.
Conclusion
The synthesis of the roundtable discussions provides a comprehensive overview of AI’s transformative impact on financial practice and regulatory processes, underscoring opportunities for innovation, efficiency gains, and enhanced compliance. Key themes include (i) AI’s role in dealing with complex regulatory frameworks and (ii) advancing analytical capabilities in compliance systems, but also (iii) requirements for the design of ethical and law-compliant AI solutions, as well as (iv) the mutual reinforcement of RegTech and SupTech. While AI presents unprecedented opportunities, challenges such as regulatory fragmentation, technical robustness and reliability, and ethical considerations require careful consideration. Moving forward, collaboration between stakeholders, regulatory clarity, and robust governance frameworks will be critical in harnessing AI’s full potential while safeguarding against the associated risks. The insights from the roundtable discussions offer a starting point for various stakeholders, including financial institutions, technology providers, and financial regulators, to delve into issues related to AI and the resulting evolving landscape of financial regulation in a responsible and effective manner. With continued advances in AI, its integration into regulatory practices, if supported by adequate governance, holds promise for shaping a more resilient, efficient, and tech-savvy financial ecosystem.
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Perspectives on Generative AI in Financial Services
Article written by James Bowden, Mark Cummins, Godsway Tetteh from the University of Strathclyde.
Note: Aligning with the Generative AI focus, segments of this blog were generated by ChatGPT using notes taken on the day capturing the presentations and discussions. The authors edited this generated content accordingly.
Presentation Highlights
We are delighted to share some highlights and discussion points from the “Generative AI for Financial Services” event held at the University of Strathclyde in Q4 2023. This event provided an important platform for in-depth discussions and explorations surrounding Generative AI and potential applications in the financial services industry.
The session commenced with Martin Robertson (Chief Commercial Officer) of Level E Research, who offered useful insights into the innovative utilisation of Discriminative AI within Level E’s automated investment strategy offerings. The core emphasis here was on the critical role of explainability in building transparency and trust with investment clients. Martin expertly differentiated between Generative AI and Discriminative AI, sparking thought-provoking discussions regarding the creative potential of Generative AI, especially in the context of content generation.
Following this, our co-organiser, James Bowden (Lecturer in Financial Technology, University of Strathclyde), delved into an extensive exploration of Generative AI applications in the financial services sector. He thoughtfully delineated the associated risks, which included concerns related to data privacy, cybersecurity vulnerabilities, embedded bias, explainability limitations, and implications for financial stability.
Annalisa Riccardi (Senior Lecturer in Mechanical and Aerospace Engineering, University of Strathclyde) then took to the stage to demonstrate a clever use case of Generative AI applied to automate satellite scheduling, with a particular focus on enhancing explainability. Drawing on this discussion, Annalisa then unveiled ongoing research at the University of Strathclyde, conducted in collaboration with Mark Cummins (Professor Financial Technology, University of Strathclyde), James Bowden and Hao Zhang (Research Associate, Financial Regulation Innovation Lab, University of Strathclyde), which is leveraging Generative AI for earnings call analysis.
The engaging presentation session was brought to a close with Blair Brown’s (Senior Knowledge Exchange Fellow in Electronic and Electrical Engineering, University of Strathclyde) insightful overview of AI regulation, standards, and trustworthiness. Drawing from an engineering perspective and its relevance to the financial services sector, Blair emphasised the crucial role of human-AI oversight and interactions, spanning human-before-the-loop, human-in-the-loop, and human-over-the-loop scenarios.
Discussion Insights
These thoughtful presentations provided a solid foundation for the rich participant discussions that followed. These exchanges were marked by their liveliness and content-rich discussions, offering valuable insights from both practical and academic perspectives. The key themes covered in these discussions included:
- Firm-Level Regulatory Responsibility and Compliance:
- The group emphasised the importance of regulatory compliance in the financial services sector, particularly concerning the use of Generative AI as a nascent technology. As the responsibility for regulatory compliance lies with the financial firm, this may incentivise in-house Generative AI development. The emerging approaches to AI regulation within the UK and the EU in particular provide frameworks within which to consider the responsible and regulatory compliant use of Generative AI within organisations.
- Data Protection and Zero Tolerance for Breaches:
- Due to the potential for significant fines, there is zero tolerance for data breaches in financial services. Data protection and consumer protection were key concerns around Generative AI, with different standards and datasets complicating matters. Options around private and localised installations of Generative AI systems need to be considered.
- Ethics and Accountability:
- Participants discussed the ethical dimension of AI in finance and the need for accountability. They suggested that CEOs and wider Boards of Directors should be held responsible if ethical breaches occur from the use of Generative AI, and governments might need to force companies to self-regulate with severe penalties for non-compliance.
- Regulatory Framework and International Challenges:
- The group highlighted the challenges of creating AI regulation in the EU when a significant portion of the AI market is based in the US, which is particularly the case in respect of Generative AI innovation. The discussion touched on principles-based regulation and the potential shift toward hard regulation, citing the General Data Protection Regulation (GDPR) as an example.
- Traceability and Auditability:
- The need for traceability and auditability in AI decision-making was discussed. The presence of an accountable human in the process was emphasised, and there was a concern about the lack of understanding of material risks in Generative AI.
The collective knowledge shared at this event provides important perspectives on the future of Generative AI in the financial services sector. The discussion provides an impetus to the research and innovation ambitions of University of Strathclyde in respect of cutting-edge Generative AI research and industry engagement, while the importance that emerged around regulatory considerations motivates an important direction of travel for the Financial Regulation Innovation Lab in terms of its AI and Compliance priority theme, which focuses on Utilising emerging technologies to simplify compliance process and monitoring.
About the Authors
Professor Mark Cummins is Professor of Financial Technology at the Strathclyde Business School, University of Strathclyde, where he leads the FinTech Cluster as part of the university’s Technology and Innovation Zone leadership and connection into the Glasgow City Innovation District. As part of this role, he is driving collaboration between the FinTech Cluster and the other strategic clusters identified by the University of Strathclyde, in particular the Space, Quantum and Industrial Informatics Clusters. Professor Cummins is the lead investigator at the University of Strathclyde on the newly funded (via UK Government and Glasgow City Council) Financial Regulation Innovation Lab initiative, a novel industry project under the leadership of FinTech Scotland and in collaboration with the University of Glasgow. He previously held the posts of Professor of Finance at the Dublin City University (DCU) Business School and Director of the Irish Institute of Digital Business. Professor Cummins has research interests in the following areas: financial technology (FinTech), with particular interest in Explainable AI and Generative AI; quantitative finance; energy and commodity finance; sustainable finance; model risk management. Professor Cummins has over 50 publication outputs. He has published in leading international discipline journals such as: European Journal of Operational Research; Journal of Money, Credit and Banking; Journal of Banking and Finance; Journal of Financial Markets; Journal of Empirical Finance; and International Review of Financial Analysis. Professor Cummins is co-editor of the open access Palgrave title Disrupting Finance: Fintech and Strategy in the 21st Century. He is also co-author of the Wiley Finance title Handbook of Multi-Commodity Markets and Products: Structuring, Trading and Risk Management.
Email: mark.cummins@strath.ac.uk
Web: University Profile for Professor Mark Cummins
LinkedIn: Mark Cummins – Professor of Financial Technology – University of Strathclyde | LinkedIn
Dr. James Bowden is Lecturer in Financial Technology at the Strathclyde Business School, University of Strathclyde, where he is the programme director of the MSc Financial Technology. Prior to this, he gained experience as a Knowledge Transfer Partnership (KTP) Associate at Bangor Business School, and he has previous industry experience within the global financial index team at FTSE Russell. Dr Bowden’s research focusses on different areas of financial technology (FinTech), and his published work involves the application of text analysis algorithms to financial disclosures, news reporting, and social media. More recently he has been working on projects incorporating audio analysis into existing financial text analysis models, and investigating the use cases of satellite imagery for the purpose of corporate environmental monitoring. Dr Bowden has published in respected international journals, such as the European Journal of Finance, the Journal of Comparative Economics, and the Journal of International Financial Markets, Institutions and Money. He has also contributed chapters to books including “Disruptive Technology in Banking and Finance”, published by Palgrave Macmillan. His commentary on financial events has previously been published in The Conversation UK, the World Economic Forum, MarketWatch and Business Insider, and he has appeared on international TV stations to discuss financial innovations such as non-fungible tokens (NFTs).
Email: james.bowden@strath.ac.uk
Web: University Profile for Dr. James Bowden
LinkedIn: James Bowden – Lecturer in Financial Technology – Strathclyde Business School | LinkedIn
Dr. Godsway Korku Tetteh is a Research Associate at the Financial Regulation Innovation Lab, University of Strathclyde (UK). He has several years of experience in financial inclusion research including digital financial inclusion. His research focuses on the impacts of digital technologies and financial innovations (FinTech) on financial inclusion, welfare, and entrepreneurship in developing countries. His current project focuses on the application of technologies such as Artificial Intelligence to drive efficiency in regulatory compliance. Previously, he worked as a Knowledge Exchange Associate with the Financial Technology (FinTech) Cluster at the University of Strathclyde. He also worked with the Cambridge Centre for Alternative Finance at the University of Cambridge to build the capacity of FinTech entrepreneurs, regulators, and policymakers from across the globe on FinTech and Regulatory Innovation. Godsway has a Ph.D. in Economics from Maastricht University (Netherlands) and has published in reputable journals such as Small Business Economics.
Email: godsway.tetteh@strath.ac.uk