Data-driven insights and news
on how banks are adopting AI
26 November 2024
On November 21, we hosted 40+ subject matter experts and industry practitioners for an in-depth discussion of AI x Banking. The entire 380 minutes of content is archived here for reference, but for those that are looking for the top-10 highlights, please see below.
Teresa Heitsenrether (JPMorganChase) gave us a glimpse of where she believes the state of AI at JPMorganChase will advance in the coming year, based on the flywheel unlocked when technical knowledge collides with operational expertise.
Prem Natarjan (Capital One) countered the narrative that productivity gains are the strongest drivers of AI use cases. In a very elegant way, Prem explained that measuring the unhyped potential for AI systems lies in their ability to transfer the cognitive burden from humans to machines.
Manny Roman (PIMCO) weighed in on the extent and the timing of AI’s disruptive impact on the economy through the lens of his own business.
Gabriel Stengel (Rogo) outlines how different banks will deploy different use cases—depending on the calculus of what drives productivity versus what drives revenue.
Ian Bremmer (Eurasia Group) forcefully pushed back against the emerging narrative that a Trump administration might retain some of the current administration’s scrutiny of Big Tech, which led to this week’s proposal for Google to sell off its Chrome browser.
Özge Yeloğlu (CIBC) discuss the culture banks need to foster to balance experimentation versus results-driven resource allocation.
Ned Carroll (PNC) challenged the conventional wisdom that promising AI tools should be deployed rapidly to entry-level and junior staff—before experts and senior contributors establish best practices for where Gen AI can help (vs. hurt) established workflows.
James Wise (Balderton Capital) outlines a fork in the road for financial institutions considering their strategic approach to future investments in emerging technologies.
Giuseppe Nuti (UBS) shares how reinforcement learning frees banks from the limitations of predictive analytics, questioning whether past performance is the best predictor of future performance (especially in today’s operating environment).
Sumitra Ganesh (JPMorgan Chase) shares her “training wheel” approach to fostering agentic AI systems as researchers cautiously shift their focus from reactive to proactive systems.
