🧾AI in Financial Compliance and Regulatory Reporting

Financial institutions must turn complex regulatory requirements into accurate reports, effective controls and accountable decisions. AI in Financial Compliance and Regulatory Reporting explores how Artificial Intelligence can support this work through better data analysis, earlier identification of problems and more efficient compliance workflows.

This course focuses on European financial services, particularly EU reporting frameworks and supervisory practices. Across eight lessons, you will explore regulatory data quality, validation and lineage, capital and liquidity reporting, transaction and position reporting, internal controls, policy mapping, regulatory change, conduct monitoring and AI governance. Practical examples include the MiFID II and MiFIR framework, EMIR and SFTR.

Throughout the course, the emphasis is on reliable evidence, professional judgement and responsible implementation. You will learn where AI adds value, where established rules and calculations remain more suitable, and how organisations can manage inaccurate outputs, bias, model risk, privacy and supplier dependencies.

The course also examines possible future developments, including AI agents, continuous monitoring, integrated reporting and supervisory technology, while distinguishing established practices from predictions.

Designed for compliance professionals, regulatory reporting teams, risk managers, auditors, governance practitioners and financial technology specialists, this course provides a practical, non technical understanding of AI’s role in financial compliance.

Please note: This course has a European focus and does not provide a comprehensive guide to every European jurisdiction. EU and UK requirements are distinct, and applicability varies by institution, activity and reporting regime. Learners outside Europe can draw on the operational and governance principles while referring to the requirements applicable in their own jurisdiction.