Overview
A 5-week course that explores how AI is transforming financial services, providing regulators, supervisors, and policymakers with a practical understanding of how AI is being adopted within industry and equip them with the tools to address evolving risks, opportunities, and regulatory challenges. Designed to ensure globally equitable adoption, the course offers a structured framework to oversee and responsibly utilise AI in digital financial services.
Next cohort: 1 June 2026
Duration: 5 weeks
Language: English
Time commitment: 5-6 hours per week, self-paced online
Fee: $2,200
Explore the course
Overview
This course is informed by the AI in Financial Services 2030 Global Research initiative, conducted in collaboration with the Bank for International Settlements, World Bank, International Monetary Fund, World Economic Forum, Inter-American Development Bank, Arab Monetary Fund and CGAP and a broad network of research and ecosystem partners.
AI is transforming financial services, risk management, supervision, and policy at a pace that challenges traditional regulatory capacity. Authorities require new skills, frameworks, and tools to understand, assess, and govern AI applications while enabling innovation, stability, consumer protection and inclusion.
Delivery format
Weekly modules
Five weekly modules delivered online.
Live expert lectures
Live expert lectures complemented by interactive sessions and case studies.
Mentorship scheme
Mentorship scheme to provide structured feedback on Capstone project.
Extended resource access
Three months of additional digital resource access.
5-6 hours per week
Time commitment: approximately 5 to 6 hours per week.
Built for public leaders
Designed specifically for public sector leaders, with no technical background required.
What the course covers
Week 1: An Introduction to AI in Financial Services
Illustrate the core concepts, evolution and value chains underpinning AI in financial services, the resulting risks, opportunities and open challenges and their relevance to regulatory and supervisory objectives.
Week 2: AI in the Financial Services Industry
Show how AI is reshaping traditional and fintech business models, operational processes, and risk profiles across financial services sectors from payments, credit, banking and capital markets to big tech and superapps, and illustrate their implications for supervisory oversight.
Week 3: AI Tools, Tech and Vendors
Investigate how the core technologies, tools and vendors are being deployed across the AI supply chain, distinguish between classical, generative and agentic AI systems, and assess how these technologies are designed and governed in production across industry, regulators and the wider economy.
Week 4: AI Risks, Governance, Regulation and Policy
Examine the existing and emergent risks and supervisory challenges posed by the rapid adoption of AI within the financial services industry. Develop a clear understanding of how to systematically think about the supervisory and regulatory implications of AI across different financial activities. Get up to speed with the latest regulatory and policy developments from around the world, tracing the rapid developments at both national, regional and international levels.
Week 5: AI Adoption and Impact within Public Authorities
Identify and evaluate internal applications of AI within regulatory institutions across policy, research, licensing and authorisation, supervision and enforcement, macro-prudential research and analysis and international co-operation approaches. Assess the institutional enablers required for their responsible, effective and sustainable adoption.
Capstone Project: develop a practical AI initiative for your institution
The Capstone Project is the culminating component of the course, enabling you to apply course frameworks to a real challenge within your institutional context.
Throughout the course, you will develop a practical initiative aligned with your authority’s supervisory, policy or operational priorities, translating course insights into clear, actionable strategies.
Unidentified AI challenge
Identify an AI-related challenge or opportunity within your institution.
Apply frameworks
Apply regulatory, governance and risk frameworks explored in the course.
Design initiative
Design a practical initiative or policy approach suited to your jurisdiction.
Outline implementation
Outline steps for responsible implementation.
Responsible AI initiative
Create a practical, policy-driven AI solution.
Example project themes
You may explore initiatives such as:
- supervisory approaches to AI systems used by financial institutions
- AI governance and vendor oversight frameworks
- supTech applications for supervisory analytics
- institutional strategies for AI adoption within regulatory authorities
- policy recommendations for responsible AI deployment in financial markets
Expert mentoring and peer collaboration
You will develop your Capstone project with guidance from course mentors and through collaboration with peers from regulatory authorities worldwide.
Benefits
This course combines rigorous academic insight with practical regulatory experience and real-world case learning.
You will:
- gain access to academia and industry experts
- become a member of a global regulatory community – Regulatory Knowledge Exchange
- understand foundational and emerging AI techniques, including agentic systems
- gain confidence to interrogate, assess, and supervise AI systems and vendors
- learn how AI and data tools can support supervisory and policy functions
- explore AI use cases across banking, payments, insurance, markets, and FinTech
- apply risk, governance, transparency, and accountability frameworks
- develop a practical institutional AI initiative as a Capstone project
- access global peer learning and regulatory knowledge resources
- earn a Certificate of Completion issued by Cambridge Judge Business School Executive Education upon successful completion and presentation of the Capstone project
Who should attend
Senior officials and technical teams across:
- central banks
- financial supervisory authorities
- securities and market regulators
- ministries of finance and digital economy
- data, analytics, IT, and innovation units
Suitable for both technical and non-technical professionals.
Course leadership and module leads
Delivered by CCAF faculty and senior policy and supervisory experts as well as top AI technical experts with contributions from international institutions and leading practitioners.
Bryan Zhang
Co-founder and Executive Director, CCAF
Bryan is a globally recognised leader in FinTech and regulatory innovation and Co-Founder and Executive Director of the Cambridge Centre for Alternative Finance at the University of Cambridge.
Kieran Garvey
AI Lead, CCAF
Kieran is a FinTech and AI regulatory leader with over 15 years’ experience strengthening the capabilities of more than 300 financial authorities across 120+ countries
Keith Bear
Fellow and Digital Assets and Distributed Ledger Technology Expert, CCAF
Keith is Chair of the Cambridge Digital Asset Research programme, specialising in digital assets, AI and fintech innovation. He previously led IBM’s global Financial Markets business and serves on the advisory boards of five fintech firms.
Douglas Arner
Associate Director of Research, CCAF
Douglas is a globally recognised authority on FinTech, digital finance and financial regulation. He has authored 20+ books and 200+ publications and leads the world’s largest FinTech online course with 130,000+ learners worldwide.
Leigh Shlomovich
Head of Research, Alpha Level
Leigh is Head of Research at Alpha Level and Founder of Nightingale Research, specialising in data science and applied statistics. They hold a PhD in Statistics from Imperial College London and have previously worked as a Senior Data Scientist at Fuse Energy and Securonix.
Sahan Bulathwela
Lecturer in AI for Biomedicine and Healthcare, University College London
Sahan is an AI researcher affiliated with the UCL Centre for Artificial Intelligence and is part of the UNESCO Chair in Artificial Intelligence at UCL. His work focuses on applying AI to sustainable education, knowledge management, and large-scale data systems.
Gary Ang
Founder, Quantitative and ex-MAS AI Risk Lead & Investment Risk Head
Gary is an AI and quantitative finance specialist who led AI risk supervision at the Monetary Authority of Singapore and developed Singapore’s first AI risk management guidelines for the financial sector. He holds a PhD in Computer Science and teaches AI and machine learning to central bankers and policymakers.
Nolwazi Hlophe
Senior FinTech Specialist, FSCA South Africa
Nolwazi is a financial regulation specialist with over a decade of experience shaping South Africa’s regulatory frameworks for innovation and consumer protection. Her work focuses on AI in finance, decentralised finance, and open finance.
Nico Lauridsen
Research Fellow, Florence School of Banking and Finance
Nico is a Research Associate at the Florence School of Banking and Finance at the European University Institute and scientific coordinator of the EU Supervisory Digital Finance Academy for SupTech and AI supervision.
Caroline Malcolm
Strategic Advisor on AI and Digital Markets, CCAF
Caroline is a global expert on fintech, AI and digital assets and Strategic Advisor at the Cambridge Centre for Alternative Finance. She previously served as Vice-President of Global Policy at Chainalysis and founded the OECD’s Global Blockchain Policy Centre.
Course start
1 June
2026
Frequently asked questions
What is the AI in Financial Services for Public Authorities course about?
The AI in Financial Services for Public Authorities course is a 5-week online course designed to help regulators, supervisors, and policymakers understand how artificial intelligence is transforming financial services.
You will gain practical insight into AI technologies, their adoption across financial markets, and the governance and regulatory frameworks required to oversee their responsible use. The course equips public authorities with the knowledge needed to respond confidently to the opportunities and challenges created by AI.
Who is this course designed for?
The course is designed for professionals working in public authorities and regulatory institutions, including:
- central banks
- financial supervisory authorities
- securities and market regulators
- ministries of finance and digital economy
- data, analytics, IT, and innovation units
The course welcomes both technical and non-technical professionals seeking to strengthen their understanding of AI in financial services.
Do I need a technical background in AI or data science?
No technical background is required.
The course is designed specifically for public sector leaders and professionals who need to understand the strategic, operational and regulatory implications of AI. It focuses on practical understanding rather than technical coding or engineering.
How long is the course and what is the expected time commitment?
The course runs for 5 weeks and is delivered fully online.
You should expect to dedicate approximately 5–6 hours per week to lectures, learning materials, discussions and assignments.
How is the course delivered?
The course combines several learning formats designed to support practical, collaborative learning, including:
- online learning through a virtual learning environment
- live sessions with global experts
- real-world case studies
- knowledge checks and reflection exercises
- moderated peer discussions
- a mentored capstone project
Together, these elements create an engaging learning experience for professionals across the global regulatory community.
When does the next cohort start?
The next cohort is scheduled to begin in May 2026.
How much does the course cost?
The course fee is USD 2,200.
What research informs this course?
The course is informed by the AI in Financial Services 2030 global research initiative, developed in collaboration with international organisations including the Bank for International Settlements, World Bank, International Monetary Fund and the World Economic Forum.
This research foundation ensures the course reflects the latest developments in AI adoption, governance and policy across global financial systems.
How can I get more information or contact the course team?
For further information about the course or the application process, please contact the course team:
A course advisor will be able to provide additional details and discuss how the course can support your organisation’s objectives.