How to Create Value from AI Today

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On-Demand Webinar

GenAI and ML technologies can help banks and credit unions compete and thrive in today’s competitive landscape, but only for organizations that have trusted, accessible data. Banking leaders need to act today to curate a data estate that is ready for the promise and opportunity in Machine Learning, Predictive Analytics, and Generative AI.

In this panel presentation, you will learn how Camden National Bank built a modern data architecture with trusted, well-governed data and is preparing for advanced data applications and AI. Camden National Bank’s technology partners will discuss some of the most promising use cases for regional banks and credit unions and will discuss how to kickstart high-impact AI- and ML-focused engagements at your institution. You will leave with a solid understanding of what technologies are available, and how they can be applied immediately to drive operational efficiencies and revenue growth.

Key Takeaways:

  • Better understand and define the GenAI, AI, and ML technologies that are driving innovation today.
  • Unlock troves of data and insights that are sitting unused in your current data storage with secure Generative AI applications.
  • Identify ML and AI applications that can be applied to use cases across all business lines.
  • Learn how you can own your data estate with a modern data architecture that gives you control of your data assets and strategy today and in the future.

Webinar Panelists:

  • Josh Nash – SVP and Director of IT, Camden National Bank
  • Greg Spencer – Director of Financial Services, Passerelle
  • Jason Bishop – Senior AI Solutions Consultant, Qlik
  • Anil Sharma – Sr. Partner Solutions Architect for Worldwide Banking, AWS
  • James McGeehan – Head of Banking and Capital Markets, Snowflake
  • Jim Marous, Host of the Banking Transformed Podcast and Co-Publisher of The Financial Brand

Watch now by completing the registration form.

SPONSORED BY: “Passerelle

 

Watch this Free On-Demand Webinar from Passerelle Data

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