Opening & Welcome
Andrew Delaney, President & Chief Content Officer, A-Team Group

Opening Keynote: The challenges and opportunities of agentic AI in capital markets

• What is agentic AI and how is it different to GenAI?
• What are the use cases for Agentic AI in capital markets and how transformative will this be?
• How is HSBC leading innovation in the AI agent space
• How can capital markets realise the full potential of Agentic AI and when will the industry get there?

Dara Sosulski, Head of Artificial Intelligence and Model Management, Markets & Securities Services, HSBC

Keynote User Panel: How to move GenAI from POC to production

• What applications/use cases are mature enough to move into production for internal or external use?
• What are the challenges of moving from a proof of concept (POC) into production and how can these be addressed?
• Embedding ML Ops: How should firms address the technical complexities and workflow integrations?
• How should firms organise governance and teams to allow central control/oversight, whilst also allowing business units to initiate applications?
• Who is in the Generative AI team – what are the key skills and capabilities required?
• How can costs be optimised and what metrics should firms use to measure success?

Moderator: Andrew Delaney, President and Chief Content Officer, A-Team Group
Nirav Shah, Senior Executive Director, Asset Management Research Technology, J.P Morgan Asset Management

Keynote: TurinTech AI

Panel: Data as a differentiator – How to build a strong data foundation for trusted AI

• How can firms improve data discoverability and accessibility for continuous data curation?
• How should firms address data inconsistencies and ensure clean and high quality data sets for AI model inputs. How can AI tools be applied to assist with this?
• What are the critical components of a robust data governance framework that can support reliable and trustworthy AI models?What are the key skills and capabilities needed for AI and how should these be sourced and retained?
• Working with 3rd parties: How should firms manage external (cloud) data vs. internal (on-prem) data with regard to data & model ownership, vendor contract compliance and risks around operational resilience?
• Responsible AI: How can firms pull all of this together to ensure responsible use of AI and a positive approach to privacy and ethics?

Eugenia Shynkevich, Head of Quant Solutions, Senior Vice President, BNY
Kevin Keenan, Senior Director, Data Science, Smarsh

Keynote: 

Panel: Deploying AI tools and models into legacy infrastructures and workflows

• Build vs. buy AI apps: What are the advantages and limitations of each approach?
• How best can firms evaluate existing third-party tools and platforms in the marketplace?
• Cloud, on premise or hybrid: how do you decide where to host your compute?
• What is the optimal set up for a cost effective and scalable data architecture?
• What are the roles of open source, RAG and vector databases in adding AI to existing infrastructure and workflows?
• What are the concerns about the carbon emissions cost of adopting LLMs and GenAI apps and how can they be approached?
• How should firms concurrently balance the costs, ethical risks and environmental/carbon impacts of AI?

Geoff Larkin, Head of Technology, Impax Asset Management
Representative from TurinTech AI

Keynote: A Regulator’s perspective on AI

• How does the current regulatory framework support AI and is any further clarification needed?
• How is the Regulator continuing to invest in data and technology to support digital markets and responsible AI?
• What are the regulatory expectations around data quality and data lineage for AI and how should firms prepare?
• What are the priorities and key messages for firms as they develop AI compliance strategies?

Ed Towers, Head of Advanced Analytics & Data Science Units, FCA

Panel: Best practices for model risk management, security and performance

• What are the challenges in testing models and what are the tools and practices that can enhance efficiency and effectiveness of testing?
• What are the challenges and solutions for managing model performance over time?
• How do you ensure the accuracy and reliability of models?  What are the strategies to manage hallucinations, ethics and bias?
• How is the threat landscape for LLMs evolving and how should firms manage model security, shadow AI and threats from jailbreaking?
• Models are costly to develop and maintain, how can costs be reduced by optimizing model performance?

Moderator: Harsh Prasad, Principal & CEO, Qexplain
David More, Senior Data Science Product Manager – Chief Data and Analytics Office, Lloyds Banking Group
Justin Xu, Managing Director – Head Of Investments, Millennium Global Investments Ltd

Keynote: Big Tech – The future of AI

• What’s coming next? How will AI continue to shape capital markets?
• What can we learn from other industries?
• The intersection of AI and quantum

Symon Garfield, Director Capital Markets Advisory & Digital Strategy, Worldwide Financial Services, Microsoft

Hear real world applications of AI and how it is being applied for efficiencies and business value.

Front Office and Trading Technology:

• Use Case Drill Down: How AI can improve transaction and communications surveillance outcomes
• Use Case Drill Down: Using AI to improve trade matching rates and reduce reconciliations
• Use Case Drill Down: Using AI in the data discovery process for deal making and portfolio management
• Use Case Drill Down: Leveraging AI to deliver data-driven market intelligence and insights for the buyside
• Use Case Drill Down: Using AI to scour descriptive information and source liquidity in OTC markets

Problem solving case #1: How to build an AI agent using RAG and Plugins – for developers and engineers

Nirav Shah, Senior Executive Director, Asset Management Research Technology, J.P Morgan Asset Management

Problem solving case #2:

Problem solving case #3:

Problem solving case #4:

Closing Keynote: The intersection of AI and Quantum: Applications to financial markets.

• What is quantum computing?
• What does the intersection of quantum computing and AI involve?
• How is quantum AI used in applications involving financial markets?
• What is the future of quantum AI for financial markets?

Dr. Del Rajan, Senior Quantum Scientist, Global Innovation, HSBC

Networking Reception

Ends 

Agenda subject to change