Market surveillance in 2026: A Q&A with LSEG experts on regulation, data and technology

Market surveillance teams are tasked with a challenging mandate - to detect market abuse, protect market integrity, and meet regulatory expectations. The quickly evolving nature of the trading environment in recent years has only added complexity. Regulatory divergence, new asset classes, rising data volumes and accelerating market velocity are now reshaping both risk and opportunity.

To understand the practical implications for those involved in market surveillance, three experts in regulatory compliance, quantitative analytics and commercial strategy at LSEG share their perspectives.

What we’re seeing is a rapid evolution in market structure alongside increasing regulatory divergence. 

In parallel, extended trading, digital assets, and alternative trading venues are changing how and where activity occurs. The positive thing here is that surveillance teams gained significant exposure into navigating the extreme volatility and market fragmentation during the past few years and this has strengthened their position for the future in a more proactive way.

Compliance and risk leaders are under pressure to demonstrate that controls are not only in place, but working as intended. When surveillance teams spend large amounts of time triaging alerts rather than analysing behaviour, that assurance becomes harder to provide. Closing this gap requires systems that are designed to scale with data growth, adapt to changing market conditions, and surface meaningful risk earlier. 

MP:  Absolutely. What we see emerging is a streamlined workflow, not a fully automated one. AI can help prioritise alerts, it can summarise findings and accelerate triage, but final judgement, particularly where interaction with regulators is concerned, still requires human oversight.

In the near to medium term, surveillance systems won’t be autonomously reporting suspicious activity. Instead, they’ll empower analysts with better context, faster insights and clearer recommendations, while retaining that critical “four-eyes” check.

MP:  Three stand out: data format diversity, higher data volumes and ecosystem fragmentation.

First, format diversity is largely a legacy issue.  Different venues and vendors describe orders and trades differently. Regulatory initiatives like MiFID II and RTS 22 have helped standardise outputs, but unstructured and semi-structured data remains a challenge. This is solvable with good data architecture, but it must be designed properly.

Second, data volumes have roughly doubled since the peak of COVID volatility. More data gives a more accurate picture of what “normal” looks like, which improves statistical detection. But there’s a catch. If technology doesn’t evolve at the same pace, performance starts to go backwards. Firms relying on legacy systems will see latency increase just as markets demand faster responses.

DK:  Alert latency is critical as both from regulatory and market oversight perspectives alerts need to be reviewed and actioned in near real time. The right technology and appropriate statistical detection are critical, Otherwise, teams face ‘alert fatigue’, higher costs and greater regulatory risk.

MP: The third big challenge is ecosystem fragmentation.  This becomes an advantage if you can consolidate it properly. Surveillance can’t look at a single venue or asset class in isolation anymore. You need to link derivatives to underlying equities, positions across venues, and behaviour across markets.  Regulators increasingly expect multi-asset, cross-market surveillance. Without that, firms only ever see a partial picture.

DK:  This becomes even more important as markets move toward extended or near 24/7 trading, whether in crypto, new derivatives or alternative venues. Fragmentation (as well as lack of liquidity) creates opportunities for manipulation unless surveillance keeps pace with the ability to detect cross asset and cross market behaviour.

MP:  The root cause is poor communication between the business and technical teams. If requirements don’t capture every relevant scenario, false positives are inevitable.

The irony is that false positives then consume analyst time, leaving less capacity to feedback into system improvements. The solution is to collaborate from day one, during design, testing and post-deployment. 

The feedback loop is critical. Continuous iteration between analysts, developers and regulatory SMEs, is what keeps surveillance aligned with changing market conditions.

DK:  Not that impact market surveillance directly, but I do expect to see further changes to the transaction reporting regime. In the UK, the FCA is reforming this regime to be more proportionate and data driven. In the EU, the savings and investment union (SIU) is looking at reducing the reporting burden and simplification of this regime. We would also see possible additional fields materialising from consolidated tape initiatives.  

These will have an impact on data quality and availability. Also, the market abuse regulation for traditional MiFID instruments cannot be completely transposed for crypto assets without some sort of modification.  So, we should be ready for that adaptation. Both UK and EU are reviewing this in parallel, and so firms need to be prepared for divergences, operational changes and technology requirements. 

MP: Market abuse techniques such as spoofing and layering have become far more complex. What were once relatively simple patterns can now involve thousands of orders across multiple venues and price levels.  In view of the threat from cybercrime, modern surveillance systems need to assess market context, not just activity. Detection logic must account for where orders sit in the order book, their likely market impact, and how behaviour unfolds across instruments and venues.