Banking organizations are at a unique place and time in their evolution, as the potential of AI grows by the day. And while AI potential is greatly understood, bringing the vision to reality remains a challenge with 60% of AI projects failing to move past the pilot stage at banks globally.1 Data and AI leaders face major challenges orchestrating a trusted view of data, navigating compliance, risk, and regulations to deliver AI at scale, but with the right strategy, you don’t have to.
We'll share how to effectively build a roadmap and what key components you need in your data and analytics strategy that will expedite wide-spread AI transformations that banking organizations can use to help tackle some of the greatest challenges like credit losses, fraud detection, and anti-money laundering, as well as unlock opportunities to improve customer retention through personalization and customer churn prevention.
Join us to see how Snowflake's Data Cloud integrates seamlessly with DataRobot's AI Cloud to uniquely enable financial services organizations to evolve their businesses with AI at their core.
