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

Practitioner Innovation Keynote: Unlocking the power of AI for data driven innovation, business growth and efficiencies at BNY

• How should you set up a strategic vision for AI and deliver the data quality needed via your data infrastructure and data strategy?
• What are the opportunities and benefits of harnessing unstructured data with AI?
• How can AI drive data driven decision making to improve customer experiences, reduce costs and the regulatory burden?
• How should firms develop an AI policy to ensure responsible use of AI and a positive approach to privacy and ethics?
• How should firms identify and measure metrics for success?

Eric Hirschhorn, Chief Data Officer, BNY

C Level Panel: How to build a data strategy for AI, to mitigate risk and gain business value

• How is the role of the CDO and the CDO office evolving in the AI and GenAI world?
• How should CDOs align data strategy and AI with the broader business objectives to ensure it contributes to the firm’s value?
• How should CDOs evaluate and select the right AI technologies to support AI data strategy? What are the most important considerations in these selections?
• More specifically, how can CDOs manage the risks of poor quality data in GenAI models?
• How should CDOs create a robust framework to ensure responsible use of GenAI and a positive approach to data ethics?
• How do you measure the return on investment (ROI) of your AI initiatives? In what ways have they created value for the business?

Moderator: Julia Bardmesser, Adjunct Professor; NYU Stern School of Business; Founder and CEO, Data4Real
Yinghua Michelle Zhou, Chief Data Officer, Nuveen
Jennifer Courant, Chief Data Officer, DWS Group
Eric Chacon, Chief Information Officer, Hometap

Keynote: Leveraging modern financial data platforms for digital transformation

Modern financial data platforms can help accelerate and future proof the digital transformation of many core investment management operations. Join this session to hear more about:

• How modern data platforms accelerate digital transformation in a systematic manner
• The role of modern data platforms in enabling the phased migration of legacy mid to back office platforms
• Future proofing your data strategy to accommodate AI/ML, Gen AI, Hyper scaler and 3rd party platforms

Mahesh Narayan, Institutional Asset Management Segment Head, Arcesium

Keynote: Transforming data management and data governance with GenAI and LLMs

• What are the top challenges in managing and governing data in financial services?
• How can GenAI and LLM help organizations scale and reduce the cost of data management and data governance?
• What does data management and data governance look like with GenAI and LLM?
• How do you measure the business value of GenAI and LLM’s in data management?

Peter Ku, VP, Chief Industry Strategist, Banking, Capital Markets, Financial Services, Informatica

Panel: Designing for the future – How to simplify and modernize data architecture to unleash data value and innovation 

• Where are financial institutions on the journey to data architecture modernization and what stage of this transformation journey are most firms currently at?
• What are the most significant challenges financial institutions face in simplifying and modernizing their data architecture, and what strategies can be employed to overcome these obstacles?
• In what ways can cloud technologies be used to modernize data architecture and enhance the value of data in financial institutions?
• Beyond cloud computing, what emerging technologies hold the most promise for revolutionizing data architecture in financial services?
• What are the best practices for utilizing data marketplaces and sharing capabilities to enable innovation and reduce complexity accessing essential data?
  Where has optimizing and modernizing data architecture significantly impacted business value, including the investment required and ROI metrics?

Moderator: Brian Buzzelli, Head of Data Practice, Meradia 
Victor Dituro, Global Investment and Risk Data Lead, J.P. Morgan Asset Management
CJ Jaskoll, Chief Technology Officer, Russell Investments 
Mahesh Narayan, Institutional Asset Management Segment Head, Arcesium
Peter Ku, VP, Chief Industry Strategist, Banking, Capital Markets, Financial Services, Informatica
Thomas McHugh, CEO and Co-Founder, FINBOURNE Technology

Panel: How to set up a data products strategy to deliver business value

• What are the drivers behind the creation of data products by the business?
• How should financial institutions define and identify data products, and what are their common use cases?
• How can a CDO office create the right environment, guidance and culture to enable business development of data products?
• When considering data products, how can firms manage data ownership and ensure data quality?
• What are the data architecture requirements to successfully deliver a data products ecosystem?
• What are the challenges in operationalizing data products?
  What are the benefits of focusing on data products as an approach to accelerating data value creation?

Moderator: Elena Alikhachkina, Chief Data Officer & Industry Advisor
Andrew Foster, Chief Data Officer, M&T Bank
JC Lionti, MD and Chief Data Officer, Mizuho Americas
Brian Greenberg, Senior Director – Business Engagement Lead for Enterprise Data Management, BNY
Dr. Leslie Kanthan, CEO and Co-Founder, TurinTech AI
Nils Buer, VP of Solution Management, Stonebranch

Keynote: Accelerating financial software runtime using GenAI-powered code optimization tools

• How can GenAI-powered tools be applied in real-world scenarios to improve software performance?
• How can ML tools utilize LLMs for identifying and optimizing inefficient code segments?
• What are the implications of these performance improvements for financial systems and markets relying on QuantLib?

Dr. Leslie Kanthan, CEO and Co-Founder, TurinTech AI

Panel: Best practice approaches to self service analytics to empower users and unlock data democratization

• What are the essential elements of a self service analytics program?
• What are the challenges from the business in delivering successful self service analytics?
• How should a CDO office set up and create the right environment and culture to enable self service analytics?
• How can firms balance innovation in analytics with appropriate data controls and entitlements?
• How can data quality management and metrics be implemented to ensure self service analytics are underpinned by trusted data?
• How can AI be applied along the data value chain to fix issues and help firms scale self service analytics? What new data governance challenges does the use of AI bring?

Moderator: Adrian Sharp, Editor, A-Team Group
Ellen Gentile, Enterprise Data Quality Team Leader, Edward Jones
Arvind Joshi, Head of Data Governance & Analytics, Rockefeller Capital Management
Adam Houhoulis, VP/Director, Data Management Office, Federal Home Loan Bank of New York

Keynote: Future-proof your data pipelines with advanced automation

• What are the data and technology challenges for developing high performance, automated data pipelines?
• How should firms address these challenges and what are the most important considerations to get right?
• What are the pitfalls to avoid?
• What benefits and ROI can DataOps teams expect from automated data pipelines?
  

Nils Buer, VP of Solution Management, Stonebranch

Panel: Best practice approaches to data management for regulatory reporting

• What approaches are firms taking to meeting increased demands from regulators for higher quality and more granular data for reporting?
• What are the data management challenges for global firms that have to meet global and local requirements and work across multiple regulatory regimes?
• How is data standardization and harmonization progressing and what more needs to be done?
• What is the role of AI and GenAI in data management for regulatory reporting?
• How are market participants leveraging reporting data to make better decisions for the business?

Moderator: Dessa Glasser, Independent Board Member, Oppenheimer & Co.
Jehangir Abdulla, Head of Back Office Development, Schonfeld Strategic Advisors LLC
Brett Utnick, Head of Regulatory Operations, BMO Financial Group
John Carroll, Chief Operating Officer, Datactics
Catherine Sutcliffe, Regulatory Affairs Director, DSB

Panel: Towards data intelligence – how to organize, integrate and structure data for successful AI

• Where are firms on their journey of tackling data silos and creating a complete picture of the data landscape?
• What is the role of metadata in making relevant and intelligent data searchable and accessible for the business?
• How are new tools and techniques being used to unify disparate sources of structured and unstructured data?
• When considering scalability and optimizing performance, what are the considerations for database selection?
• How can data observability ensure a strong foundation for AI and what are the best practice approaches for implementation?
• As firms re-architect data stacks, should they be centralizing data governance and controls (data privacy, security) in order to mobilize data across the organization efficiently?

Moderator: Julia Bardmesser, Adjunct Professor; NYU Stern School of Business; Founder and CEO, Data4Real
Sumanda Basu, Head of Data Quality, Risk, Controls & Data Domain Lead, Societe Generale
Linda Zhang, Executive Director, Commercial & Investment Bank – Data and Analytics Technology, JP Morgan Chase
Theo Bell, Head of AI Product, Rimes

Networking drinks and Data Management Insight Awards Ceremony