By Lisa Balter Saacks

President, Trillium Surveyor

January 2026 

As we enter 2026, it’s clear that market structure is changing faster than many oversight models were designed to handle. Trading activity continues to extend beyond traditional sessions into 24/5, and in some cases 24/7, environments. Prediction markets and other event-driven instruments are scaling quickly and attracting broader participation. Alongside this growth, oversight is no longer being evaluated on outcomes but on the consistency of process, documentation and the ability to explain how conclusions were reached. That expectation is reshaping how trading and compliance teams design their processes and leverage technology to manage risk and performance in modern markets.

In response, many firms are taking a closer look at how oversight is actually organized. Surveillance, best execution, and review processes often still operate in separate systems, built on different data sets and assumptions. That inconsistency makes it harder to evaluate outcomes and explain decisions with confidence. As complexity increases, oversight models are evolving toward a more consistent data foundation across systems. This allows teams to apply the same underlying data to multiple analytics and oversight needs while maintaining clear ownership and defensible processes.

This shift is especially visible in markets tied to real-world events. Activity around major sporting events, political developments, or economic releases can accelerate quickly, drawing heightened participation and attention in short windows of time. Even amid this volatility, firms are expected to establish oversight frameworks early, ahead of market maturation and broader participation, so that decisions remain defensible as regulatory expectations catch up.

Operational pressure is also growing. Expectations continue to rise while resources do not always increase at the same pace. In that environment, automation and AI can create meaningful leverage, but only when they are grounded in clear, deterministic foundations. We believe the most effective approaches combine rules-based frameworks for repeatability and governance with AI layered on to support prioritization, review workflows, and narrative clarity. The goal is not autonomy, but explainable decision support that helps teams focus on what matters most.

All of this ultimately depends on data. As products, venues, and trading models proliferate, data quality becomes a core risk consideration. Clean, consistent, and transparent data reduces noise, improves escalation quality, and helps firms maintain trust with regulators and internal stakeholders alike.

Taken together, these themes are shaping how we think about oversight in 2026. The firms that are best positioned will be those that invest in unified approaches, design oversight with modern market structure in mind, and build resilience through clarity, consistency, and explainability.

We look forward to continuing these conversations with clients, partners, and the broader industry in the year ahead. 

Lisa Balter Saacks

President