By Michiel Verhoeven, CEO, Xceptor
Big picture
In 2026, capital markets firms will face continued regulatory pressure, operational complexity, and the need to keep pace with rapid technological change while demonstrating ROI. As a result, we expect a shift away from simple cost-cutting, tech for tech’s sake, and quick compliance fixes. The focus should be on value creation and futureproofing, with data placed at the heart of everything.
Before investing in new AI or compliance projects, institutions must first go back to basics. It’s about ensuring secure, validated, and trusted data and optimising the entire trade lifecycle – from pre-trade to post-trade settlement, plus trace to origin. By automating the process for data standardisation, firms will accelerate readiness, reduce errors, and streamline workflows.
Adapting to regulatory change
Regulatory demands across the trade lifecycle will only get tougher.
Pre-trade, firms must ensure compliance before execution. Enhanced market data analytics and real-time risk controls are critical for best execution and effective surveillance under regulations like MiFID II and MAR.
Post-trade, the shift to T+1 settlement cycles is magnifying inefficiencies. Issues that once took two days to fix must now be resolved in one. Automation, exception handling, and adaptive rule engines are essential to avoid settlement fails and penalties, while reconciliation and reporting must be digitised and auditable for transparency across the custody chain. With the FCA’s warning about readiness for Europe’s T+1 deadline (11th October 2027), and lessons learned from the US transition, firms must not delay action.
Tax reporting is also being digitised under mandates like Germany’s MiKaDiv (1st January 2027) and the EU’s FASTER Directive (1st January 2030). Manual processes will be a huge barrier. Firms must assess their data models, reporting gaps, and custody chain transparency, then automate their tax reporting and compliance processes. This will reduce manual effort and risk, while ensuring readiness for these timelines.
Delivering measurable outcomes with AI
In 2026, AI adoption will continue to dominate headlines. Yet, without a clear strategy, institutions risk creating a money pit. Firms should ask themselves: “what are our pain points and how can we achieve the necessary outcomes with AI?”. Without the right infrastructure, data management, and clarity of purpose, technology is not a magic fix.
For example, AI can drastically reduce time spent extracting information from complex tax documents, and agentic AI could augment productivity further by proactively solving problems and triggering downstream actions. But without addressing inconsistent data formats, firms will face more errors and time spent correcting them, or even financial and non-compliance risks. Issues with data reliability, quality, and flow are common causes of failed AI projects – flawed data creates flawed AI. Firms must invest in platforms that normalise, enrich, and validate data across fragmented systems before scaling AI projects.
Partnering for success
Optimising the trade lifecycle is about more than compliance – it’s about unlocking operational efficiency, reducing risk, and delivering superior client outcomes. Success in 2026 will depend on the right partnerships. Capital markets firms need technology partners with extensive industry expertise, robust capabilities, and a focus on solving real problems. In an industry with little margin for error, data automation must come with effective monitoring, visibility, and transparency. Firms will prioritise cloud-first, SaaS-ready platforms that improve data quality, reduce risk, and scale operations for the future.
