Course Catalogue

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This course provides a practical and critical introduction to the use of artificial intelligence (AI) and regulatory technology (RegTech) in financial compliance. It examines how AI-enabled tools are being deployed across compliance functions such as monitoring, customer due diligence, and regulatory oversight, and situates these developments within the legal, regulatory, ethical, and governance frameworks that shape their responsible use. Drawing on applied examples from financial institutions, FinTech firms, and supervisory contexts, the course enables learners to connect technological capability with compliance practice, organisational decision-making, and emerging regulatory expectations.

This course is delivered fully online through primarily asynchronous learning activities hosted on Moodle or other suitable VLE. Teaching is organised through a sequence of thematic modules supported by pre-recorded lectures, online quizzes, guided learning activities, and formative Capstone development tasks. Optional live online engagement may also be offered in the form of drop-in sessions or assessment support sessions. The exact scheduling, pacing, and release pattern of teaching activities may vary between course runs.

There are no formal entry requirements. The course is open to learners from a range of academic and professional backgrounds. Prior exposure to financial services, compliance, law, regulation, governance, or organisational practice may be helpful, but is not required. All core concepts are introduced in accessible language and taught from the perspective of compliance, governance, and regulatory practice.

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Capstone Project - Design Responsible AI-Enabled Compliance Solutions (100%)

The Capstone Project is the sole summative assessment for the course. It requires learners to produce an applied analysis of a real or simulated financial compliance challenge and to propose a responsible AI-enabled compliance response. The assessment integrates learning from across the course, including AI and RegTech concepts, compliance functions and organisational context, risk and governance analysis, regulatory implications, and future-oriented professional development.

Learners are required to:

■ identify and frame a financial compliance challenge;

■ propose an AI-enabled compliance solution informed by course concepts;

■ evaluate associated risks, governance requirements, and accountability considerations;

■ analyse relevant legal and regulatory implications; and

■ develop a forward-looking professional roadmap linked to future skills and organisational readiness.

Learners may base their project on the course Anchor Case or on their own professional or organisational context.

The Capstone may be submitted in one of the following formats:

■ a written report of approximately 2,500 words;

■ a professional slide deck with substantive speaker notes; or

■ a recorded presentation or narrated slide deck supported by slides and/or written notes sufficient to demonstrate equivalent analytical depth.

All formats are assessed against the same criteria and must demonstrate equivalent academic standard and depth of analysis. Full details of submission arrangements and assessment guidance will be provided in the course handbook and Moodle.

This course aims to provide learners with a practical and critical understanding of how AI and RegTech are reshaping financial compliance. It introduces core AI and RegTech concepts, examines their application across compliance functions and regulated organisational settings, and explores the legal, regulatory, ethical, and governance frameworks relevant to their adoption. The course further aims to equip learners with the analytical and professional capabilities required to evaluate AI-enabled compliance solutions, assess associated risks and regulatory implications, and develop forward-looking responses to the changing demands of compliance work in financial services.

By the end of this course students will be able to:

1. Explain core AI and RegTech concepts relevant to financial compliance, linking technological capabilities with regulatory frameworks, industry applications, and compliance challenges.

2. Analyse compliance functions and processes to identify areas where AI may add value, taking into account both organisational and regulatory aspects.

3. Evaluate risks, governance requirements, and regulatory implications associated with AI adoption in compliance contexts.

4. Design a forward-looking professional roadmap for operating effectively in an AI-augmented compliance environment, informed by regulatory trends and evolving skills demands.