The Capital Markets Data Summit 2025 is a must-attend event for Chief Data Officers, Chief Data Analysts, Chief Information Officers, and senior data leaders from investment banks and asset management firms. Focused on cutting-edge data strategies, the summit explores topics like AI-driven analytics, cloud adoption, data governance, and regulatory compliance. It offers valuable insights on how to leverage data for competitive advantage and operational efficiency, making it ideal for professionals seeking to drive innovation and align data strategies with business objectives in the capital markets.

08:30

REGISTRATION AND BREAKFAST

08:55

CMD CHAIR OPENING REMARKS

Vivienne Artz OBE FCSI (Hon), Data Strategy & Privacy Policy Advisor, Centre for Information Policy Leadership, Chair of IBDE Data and Artificial Intelligence Programme (invited)

09:00

KEYNOTE PRESENTATION: The power of Market Data: Shaping Tomorrow's Capital Markets

Key Discussion Points:

• AI and Advanced Analytics: How future technologies will transform market data into actionable insights for real-time decision-making.
• The Evolution of Data Monetization: Exploring new revenue models and the growing importance of alternative data in capital markets.
• Regulatory Horizons: Preparing for future regulatory shifts and ensuring compliance in an increasingly data-driven financial ecosystem.

09:20

PANEL: Cloud-Enabled Capital Markets: Driving Innovation Through Scalable Data Solutions

Key discussion points:

• The Cloud Revolution in Capital Markets: How cloud adoption is transforming data storage, analysis, and operational efficiency, making firms more competitive.
• Security and Compliance in a Cloud-First World: Best practices for ensuring that cloud adoption meets stringent financial regulations and security standards.
• Scaling Innovation Through the Cloud: Harnessing cloud platforms to rapidly scale AI, machine learning, and big data capabilities for faster insights and decision-making.

09:55

DEBATE: ESG Data in Capital Markets: A Reliable Metric for Sustainable Investment or a Misleading Indicator?

Key Arguments:

• For ESG Data as a Reliable Metric: Proponents argue that well-structured ESG data is crucial for assessing long-term risks, driving sustainable investment strategies, and aligning with investor demand for ethical portfolios.
• Against ESG Data as a Misleading Indicator: Critics claim that inconsistent standards, unstructured data sources, and potential greenwashing make ESG data unreliable and difficult to compare across companies and sectors.

Samuel Livingston, Head of Quantitative Strategies, Ambienta

10:10

PANEL: Mastering ESG Data: Integrating Non-Standard and Unstructured Data

Key Discussion Points:

• Data Complexity: Overcoming challenges in integrating diverse, non-standard ESG data from unstructured sources like sustainability reports, social media, and news.
• Technology Solutions: Leveraging AI, machine learning, and NLP to analyse and extract actionable insights from unstructured ESG data.
• Best Practices: Real-world examples of successful ESG data integration, ensuring transparency, quality, and consistency in investment strategies.

Anna-Marie Tomm, ESG Data Scientist, Man Group

10:45 -11:15

POP-UP COFFEE & CONVERSATION

• Attendees can grab their coffee and mingle with others at stations around the venue, fostering discussions over their favourite caffeinated beverages.
• Coffee cup sleeves will have questions or prompts to encourage conversations about the industry, creating a more dynamic networking environment.

ROUNDTABLES

11:15

Roundtable R1

Real-Time Market Data Strategy Simulation: How to build a data-driven strategy using varying levels of market data:

Outcome: Each team leaves with a data-driven strategy to make key business decisions, such as optimizing portfolios, or launching a product.

Roundtable R2

Hands On Session: How to Uncover Hidden Alpha using Alternative Data:

Outcome: Participants leave with a demonstration of data visualization tools for analysing alternative data.

HOST: Neil Sharma, Lead Data Science Analyst, Man Group

Roundtable R3

Commitment Wall: Technology Adoption in Your Organization:

Outcome: These actions are posted on a "Commitment Wall" for others to see. This final exercise encourages participants to leave with a personal commitment to driving change in their organization, ensuring that the session ends with a focus on actionable steps for tech adoption.

Roundtable R4

Future Scenarios Brainstorm: The Role of Real-Time Data in 2030

Outcome: Each group presents their future scenarios, highlighting both the positive and negative implications of real-time pricing on market transparency and fairness. 

12:00

Roundtable R1 

Diversity Policy Hackathon: Where participants design innovative workplace policies aimed at improving gender balance in the industry.

Outcome: Provides a practical exercise in creating structural change to support gender inclusion.

Roundtable R2 (Part 2)

Hands On Session: How to Uncover Hidden Alpha using Alternative Data:

Outcome: Participants leave with a demonstration of data visualization tools for analysing alternative data.

HOST: Neil Sharma, Lead Data Science Analyst, Man Group

Roundtable R3 (Part 2)

Commitment Wall: Technology Adoption in Your Organization:

Outcome: These actions are posted on a "Commitment Wall" for others to see. This final exercise encourages participants to leave with a personal commitment to driving change in their organization, ensuring that the session ends with a focus on actionable steps for tech adoption.

Roundtable R4 (Part 2)

Future Scenarios Brainstorm: The Role of Real-Time Data in 2030

Outcome: Each group presents their future scenarios, highlighting both the positive and negative implications of real-time pricing on market transparency and fairness. 

12:45 – 13:45

LUNCHTIME QUIZ AND WIN

Attendees enjoy their lunch whilst participating in a quiz about the day's topics.

STREAMS

STREAM A: REGULATIONS & DATA GOVERNANCE STAGE

STREAM B: AI & BUY-SIDE STAGE

13:45

STREAM A DEBATE: Regulations vs. Innovation: Are Strict Data Governance Policies Stifling Innovation in Capital Markets?

Key Arguments:

• For Regulations Supporting Innovation: Advocates argue that stringent data governance and regulatory frameworks provide necessary safeguards, promoting market integrity, investor protection, and fostering trust in financial institutions, which ultimately encourages sustainable innovation.
• Against Regulations Stifling Innovation: Opponents contend that overly strict data governance policies create excessive compliance burdens, slow down the adoption of cutting-edge technologies like AI and blockchain, and limit the agility needed to compete in a rapidly evolving financial landscape.

STREAM B DEBATE: AI in Capital Markets: A Game Changer or a Regulatory Minefield?

Key Arguments:

• For AI as a Game Changer: AI offers unmatched potential in transforming trading strategies, market forecasting, and operational efficiency, leading to higher returns and better risk management.
• Against AI as a Regulatory Challenge: The rapid advancement of AI introduces significant ethical, compliance, and data security risks, making it a challenge for regulators to keep pace with evolving technologies.

14:05

STREAM A PANEL: Data Governance in Capital Markets: Ensuring Integrity, Compliance, and Security

Key Discussion Points:

• Regulatory Compliance and Reporting: How governance frameworks help meet stringent regulatory requirements and improve data transparency.
• Data Security and Privacy: Protecting sensitive market data while managing access and safeguarding privacy.
• Ownership, Accountability, and Collaboration: Defining roles and responsibilities to foster cross-departmental cooperation and ensure data integrity.

Rickie Glasgow, Global Head of Data Governance NTAS, Northern Trust Asset Servicing

Yagmur Kanbas- Campbell, Director, Finance Controllers Data Governance, Citi

STREAM B PANEL: Unleashing the Power of Generative AI in Capital Markets

Key Discussion Topics:

• Crucial Data Requirements: Generative AI needs high-quality, diverse, and real-time data to generate accurate and actionable insights.
• Competitive Differentiators: Effective data collaboration and robust security measures enhance AI capabilities and ensure data integrity, setting organizations apart in the market.
• Impact on Finance: Generative AI transforms investment banking and asset management by improving market forecasting, personalizing investment strategies, and automating report generation.

Chief Privacy & Data Ethics Officer, BNY Mellon (invited)

14:40

STREAM A CASE STUDY: Implementing a Robust Data Governance Framework: Lessons from a thought leader

Key Discussion Points:

• Overcoming Compliance Hurdles: How the bank navigated complex regulatory requirements while ensuring data security, transparency, and accuracy across global markets.
• Aligning Data Governance with Business Goals: Strategies used to integrate data governance into operational workflows, improving decision-making and enhancing competitive advantage.
• Leveraging Technology for Data Management: The role of AI, automation, and advanced analytics in streamlining governance processes and reducing compliance costs.

STREAM B CASE STUDY: Transforming Asset Management with AI: A Case Study in Predictive Analytics

Key Discussion Points:

• AI-Driven Investment Strategies: How the firm used AI-powered predictive analytics to enhance portfolio management and improve risk-adjusted returns across diverse asset classes.
• Integrating Alternative Data: Leveraging unconventional data sources, like social media and satellite imagery, to strengthen AI models and gain a competitive edge in market forecasting.
• Overcoming Implementation Challenges: Practical insights into addressing data quality issues, integrating AI with existing systems, and fostering team collaboration during AI adoption.

15:00

STREAM A PANEL: Navigating Regulatory Challenges in Capital Markets: Insights from Auditors

Key Discussion Topics:

• DORA (Digital Operational Resilience Act): How auditors interpret the impact of DORA on operational resilience and risk management in capital markets.
• Consolidated Tape: The role of auditors in assessing transparency and compliance with consolidated tape regulations for trade reporting.
• EU Regulatory Framework & UK Needs: Adapting the EU’s evolving regulatory framework, including listing rules, to fit the post-Brexit UK landscape.
• EMEA Refit: Understanding the implications of the EMEA regulatory refit and its effect on financial reporting and compliance.

Auditors: Morgan Stanley, Wells Fargo, and Barclays 

Avanthi Weerasinghe, Principal, Capital Markets & wholesale policy, UK Finance (invited)

STREAM B PANEL: Data Quality in Asset Management: Bridging the Gap Between Technology and Investment Strategies

Key Discussion Points:

• Collaborating with Tech Teams: Strategies for influencing the tech department to develop software that meets the specific data quality needs of asset managers.
• Data Integrity: Ensuring accuracy, completeness, and timeliness in data through effective communication between investment teams and tech developers.
• Custom Solutions: Best practices for defining clear requirements and priorities to align software development with asset management goals.

15:45

POP-UP COFFEE & CONVERSATION

• Attendees can grab their coffee and mingle with others at stations around the venue, fostering discussions over their favourite caffeinated beverages.
• Coffee cup sleeves will have questions or prompts to encourage conversations about the industry, creating a more dynamic networking environment.

16:05

CASE STUDY: Data Architecture & Lineage: Aligning People, Process, and Technology

Key Discussion Points:

• Role of the Data Architect: How data architects drive the design and implementation of robust data frameworks to support asset management strategies.
• Impact on Data Lineage: Ensuring clear visibility and traceability of data flow across systems, enhancing trust and regulatory compliance.
• Integration of People, Process & Technology: Balancing team expertise, workflow efficiency, and cutting-edge tools to strengthen data architecture and lineage management.

Jeremy Posner, Lead Data Architect, (ex Fidelity), 

16:50

FIRESIDE CHAT: Bridging the Skill Gap: Preparing the Next Generation of Market Data Professionals

Key Discussion Points:

• Addressing the Ageing Workforce: Examining the impact of an ageing workforce in market data roles and the need for proactive succession planning.
• The Skill Gap in Data and Technology: Identifying key skills shortages in areas such as data analytics, AI, and cloud technologies, and how they affect market data operations.
• The Role of Market Data Academies: Showcasing successful training academies and initiatives that are equipping the next generation of professionals with the skills needed to drive innovation and growth in capital markets.

17:05

CMD CHAIR CLOSING REMARKS

17:10 – 18:10

NETWORKING DRINKS RECEPTION