By Melissa Watras, Director of Product
A common thread across many of our client conversations right now is a deceptively simple question: how do you build for a market when you don’t know exactly what that market will look like a year from now?
That feels especially relevant heading into Q4. Prediction markets continue to grow, 23/5 trading is getting closer, data requirements are changing, and firms are being asked to oversee more activity across more products and more hours.
We can’t predict every change. But we can build technology that is ready to adapt when it happens.
That has been a big part of how we’ve thought about the Surveyor platform this quarter: building flexibility for where markets are going, adding more context that helps firms understand what actually matters, and strengthening the data foundation underneath it all.
Building for What Changes Next
Prediction markets, extended-hours trading, digital assets and other market changes can feel like they bring entirely new oversight challenges. But often, the underlying behaviors we’re looking for aren’t new. What changes is how they show up.
Our approach is to take what we know from similar existing markets and the principles of good oversight, then adapt them to the product, market structure, and participants in front of us.
That takes flexible technology, and it takes a technology partner that can evovle alongside you. For us, that means keeping a close eye on how markets are changing while staying close to our clients and how their needs are evolving. Those conversations help us both respond to change and inform what we build next.
Building More Context Into Surveillance
As markets expand, simply identifying unusual activity becomes less useful on its own. The harder question is: is this actually unusual for this participant, in this market, under these conditions?
Understanding an account’s historical behavior can help identify meaningful shifts from its established baseline. But context can go further. Market history and conditions help explain what was happening around the activity, while that outcomes from prior reviews can add another layer of useful context over time.
The context that matters will differ market. In prediction markets, for example, a participant’s win rate over time could provide useful context alongside timing, size and other behavior. In extended-hours markets, liquidity, volume and session conditions may tell a different story.
Modernizing the Data Foundation
None of this works without the data underneath it.
As firms add products, venues and trading hours, the number and variety of data feeds they need continues to grow. Integrating those feeds is one challenge. Normalizing and maintaining them as markets change is another.
This quarter, we expanded our market data infrastructure with BMLL, Databento and LO:TECH, giving us more flexibility in how we bring data into Trade Surveillance and Best Ex as needs evolve.
Having that data integrated and normalized creates opportunities across more than one workflow. Surveillance, best execution, investigations and other trade lifecycle analytics often start with the same underlying activity. That opens up a much more useful question for firms: where can we use the same data to streamline responsibilities rather than build separate infrastructure every time something changes?
That becomes increasingly important as the number of markets, products and hours firms need to oversee continues to expand.
Technology Is Also a Trust Decision
There is another side of adaptability that doesn’t get talked about enough, which is who you are adapting with.
Security has to be foundational, but trust in a technology partner goes beyond a security checklist. It comes from knowing how they approach your data, that they understand your business, and that there is a responsive team on the other side when something new comes up.
And when new needs do come up, you want to know they’re being heard. Some of our most useful product conversations start with a client saying, “Here’s what we’re seeing. How should we handle this?”
Those conversations matter. Roadmaps shouldn’t be built in isolation, particularly in markets that are changing this quickly. What our clients are seeing and solving for helps shape where we go next.
What We’re Watching
Heading into Q4, I’m particularly interested in what happens as some of these changes move from planning into practice.
As 23/5 trading gets closer and prediction markets continue to grow, we’ll get a clearer picture of how participant behavior, liquidity and oversight needs evolve with them. That will give us more real world context to land, new questions to solve.
And then there’s AI. One area we’re focused on is how it can help firms make better use of the context they already have, while keeping people at the center of the decision.
Could prior judgments help inform how a similar alert is reviewed today? Could teams query years of surveillance data more naturally or use that history alongside established models to better understand which activity deserves attention?
There is a lot of opportunity there. But for us, AI doesn’t replace the foundation. It builds on it. The quality of the data, the history behind it, the models built to identify activity and the judgment of the people reviewing it all still matter.
We won’t know exactly what markets will look like a year from now. That’s the point. The goal is to have the data, technology and context in place to adapt as they evolve.
That’s what we’ll continue building toward as we head into 2027.
If you’re working through any of these same questions, or seeing something we should be thinking about, please reach out. We’d welcome the conversation, including where you see things differently.