AI presents immense opportunity and risk for Financial Services. Regulated financial services providers need to ensure that they have appropriate accountability and governance structures in place to meet the requirements of the UK regulators, including those of the Senior Managers Regime. Senior Managers must take steps to ensure that they address the impact of AI when considering whether the business is controlled effectively, relevant legal and regulatory requirements are complied with, responsibilities are appropriately delegated and required regulatory disclosures are understood and made.
This course is tailored to the needs of Senior Managers in Financial Services. Course participants will learn from experienced instructors and their fellow participants who face similar challenges in addressing AI risk in the regulated context.
Before attending, participants will receive a study guide outlining the key course materials. Lunch will be provided and a drinks reception has been arranged for the end of the day. A follow up Q&A session will take place after completion.
On successful completion Senior Managers will receive a certificate and digital badge that may be attached to online profiles confirming the training received and competence acquired.
Location
London, Pinsent Masons30 Crown Place
Earl Street
London
EC2A 4ES
Course date
TBC – to be notified when dates are confirmed, please register your interest.
Fees
TBC – With course dates confirmed, an early bird discount will be made available.
Agenda
| Thursday 23 January 2025 | AI for Senior Managers in Financial Services | |||
| Time | Session | What you will learn | |
|---|---|---|---|
| 08:30-09:00 | Registration, Breakfast and Peer Networking
An opportunity to meet senior leaders from a wide range of financial institutions. At our last iteration of the course, we had senior leaders attend from JP Morgan, Morgan Stanley, Natwest, Lloyds Banking Group, Sainsbury’s Bank, Experian, Baillie Gifford, Aegon and Brit Insurance to name a few. |
||
| 09:00-09:15 | Welcome and introduction from course leaders
During this session our course leaders set the scene with case study examples and real-life use cases of AI for financial services. |
||
| 09:15-10:30 | Session 1 | Understanding Al, the Legal and Regulatory Framework and Ethical Implications
This session includes opportunity to understand how financial institutions are responding to the legal and regulatory framework, addressing regulatory overlap issues and finding baseline approaches to compliance with requirements in the UK such as the PRA’s ss1/23, the EU AI Act and the approach taken towards model risk management in other jurisdictions. |
|
| 10:30-10:50 | Coffee break | ||
| 10:50-11:50 | Session 2 | Data Management and Accuracy, Validity and Reliability
The course leaders will draw out the technical, governance, strategy and risk framework implications of best practice approaches towards data management in the AI context and how to deal with hallucinations and other AI-specific risks. |
|
| 11:50-12:00 | Comfort break | ||
| 12:00-13:00 | Session 3 | Transparency
This session covers the topics of transparency and explainability broadly, identifies relevant regulatory requirements and technical standards and gives participants the opportunity to compare different approaches that have been implemented by financial institutions. |
|
| 13:00-14:00 | Lunch | ||
| 14:00-15:00 | Session 4 | Bias and Discrimination
As ‘traditional AI’ has been around for a number of years and genAI has just passed its two-year public landmark reveal in November 2022, these topics are well understood. However, have they been adequately addressed through policies, processes and controls and contractual provisions? In this session the course leaders will provide practical application of lessons learned. |
|
| 15:00-15:15 | Afternoon break | ||
| 15:15-16:00 | Session 5 | Monitoring and Oversight
Fundamental to AI governance and effective risk management is the broad topic of monitoring AI systems and ensuring effective human oversight and accountability across the business. This session will dive deep into different approaches that can be taken at all stages of the AI lifecycle. |
|
| 16:00-16:20 | Session 6 | Intellectual Property and Liability Implications
A quickfire session reviewing key case law developments and best practices taken across a number of jurisdictions. |
|
| 16:20-16:30 | Comfort break | ||
| 16:30-17:30 | Final session and closing | Governance Approaches and Going Forward
An opportunity to consider in detail how existing approaches to governance can be adapted to address AI risk across the entire business.
|
|
| 17:30-19:30 | Drinks and canapés | ||
Speakers
Luke Scanlon, Head of Fintech Propositions and Legal Director at Pinsent Masons has advised some of the world’s leading technology providers and financial institutions on AI legal and regulatory risk. Recognised by Chambers and Legal 500, he regularly provides training sessions and workshops on AI for Financial Services providers. He has also spoken at several conferences on AI in Financial Services, including the AI Scottish Summit, and has published extensively on the topic for publications including FT Adviser, The Sunday Times (Scotland) and The Banker magazine.
Mike is Assistant Professor of Law and Ethics at Clemson University in the United States and Affiliated Researcher at Edinburgh Futures Institute. He is currently editing a Cambridge Handbook on AI and Public Law . He also works on ways in which firms can be genuinely democratic and inclusive in their adoption and deployment of technologies.
Adam Ntakaris is a Lecturer in Financial Technology and Programme Director of the MSc in Finance, Technology, and Policy at the University of Edinburgh Business School, with extensive experience in consulting on industrial quant projects. He is also an investor in AI-focused companies. He received his DSc in HFT and AI from Tampere University under the BigDataFinance Marie Sklodowska-Curie network in 2019, his MSc in Financial Modelling and Optimisation from the University of Edinburgh in 2014, and his BA in Mathematics from Aristotle University of Thessaloniki in 2009. He was also a quant intern at Abrdn in 2014. From 2014 to 2016, he was an EIR Analyst at Citigroup Investment Bank, and from 2010 to 2013, a Maths Olympiad Coach at Systima.