Highlights from A Wealth of Intelligence, where leaders from xAI, S&P Global Market Intelligence, and AWS explored how raw data becomes real investment insight.
On September 9th, Context Analytics, A BridgeWise company, joined forces with S&P Global Market Intelligence to host A Wealth of Intelligence, an evening in New York that brought together some of the sharpest minds working at the intersection of data and markets.
The centerpiece of the evening was a fireside chat moderated by Joe Gits, CEO of Context Analytics, featuring speakers from xAI, S&P Global Market Intelligence, and AWS - three voices from very different corners of the data ecosystem.
What made the conversation compelling wasn't just the range of perspectives in the room, it was how naturally they converged on the same core idea: unstructured data is no longer a side conversation in finance. It's becoming central to how alpha gets found.
Joe opened by framing the discussion around a simple arc: input, structure, action, creating a flow that was able to demonstrate where the intersections lie.
Stephen Lynch, Business Development Lead from xAI, brought a firsthand view of the X platform's data at the source — the patterns and behaviors that show up in trending activity, how quickly volume builds around a moving story, and what that tells you about user dynamics in real time. The conversation touched on how long a trending topic tends to stay relevant to markets before the signal fades.
Mike Patton, Vice President from S&P Global Market Intelligence, picked up the thread from there, speaking to what it takes to move from that kind of raw input to something structured enough to act on, using the CA/S&P partnership as an example of that in practice. The discussion turned to the build-versus-buy decision so many firms face, the case for partnering versus building unstructured data capabilities in-house, and where in that pipeline signal most often gets lost or misunderstood.
From there, Renee Lau, Principal Financial Services Industry Strategist at AWS brought the conversation toward AI and infrastructure, the bottlenecks teams tend to underestimate when trying to operationalize alternative data at scale, and what growing data volumes mean for processing and storage as AI becomes more central to the workflow. The panel closed out riffing together on where the space is headed next.
Mike Patton (S&P Global Market Intelligence), Renee Lau (AWS), Stephen Lynch (xAI), and Joe Gits (Context Analytics, A BridgeWise Company) speaking at A Wealth of Intelligence, September 9 in New York
One thread that kept resurfacing throughout the night was the topic of exhaust data. This is data created as a side effect of other activity, rather than data created for the purpose of being analyzed. Panelists pointed to this as one of the more underexplored frontiers for alpha generation. As more of the world's activity leaves a digital trace, the question isn't whether that exhaust contains a signal - it's who builds the infrastructure to capture and structure it first.
It's a fitting note for where this conversation is heading industry-wide: less about whether unstructured and alternative data belong in the investment process, and more about how fast firms can build the muscle to use them well.
A huge thank you to Stephen, Mike, and Renee for such a thoughtful conversation, and to everyone who joined us. Conversations like this one are exactly why events like A Wealth of Intelligence matter - they get people who normally operate in different lanes talking to each other, and the ideas that come out of it are better for it.
