A-Team Insight Author: Rollings Nicole
FCA Sanctions Review Puts Control Evidence at Centre of Screening Debate
The FCA’s latest sanctions review raises the bar for firms to prove that screening systems, data feeds, alert workflows and vendor arrangements work under live sanctions conditions. The review draws on the FCA’s assessment of more than 150 supervised firms since February 2022. It includes examples of good and poor practice across governance, management information,...
Duco Unveils Tool-Surface Architecture to Make Agents Auditable in Post-Trade
In agentic post-trade, explainability remains one of the hardest problems to solve. Agents can already read systems, draft exceptions, propose amendments and assemble workflows. What they have struggled to do – in a way that satisfies a Head of Operations facing a regulator – is leave behind an audit trail that survives scrutiny. Duco’s launch...
Testing an Assumption: Do AI Signals Really Decay?
Alpha decay is one of the foundational assumptions in quantitative finance. The empirical literature, beginning with McLean and Pontiff’s 2016 study of 97 anomalies and replicated and refined across multiple subsequent studies, has repeatedly found that returns degrade out-of-sample and degrade further once published. The assumption sits inside almost every institutional model risk framework as...
Scraping at Scale: Where AI Actually Helps, and Where It Doesn’t Yet
“AI web scraping that doesn’t break” was the title given to a fireside chat at the recent A-Team/Eagle Alpha Alternative Data Conference London – a phrasing that is, on its own terms, aspirational. Pipelines that self-maintain through site changes, schema drift and content shifts remain a destination rather than a current reality, and the session...
AI in Capital Markets Handbook 2026: From Experimentation to Governed Execution
Capital markets firms are under pressure to convert AI experimentation into sustainable business value. The challenge is not simply finding use cases but demonstrating that AI can support regulated workflows through approved data, accountable ownership, measurable outcomes and defensible evidence. A-Team Group’s AI in Capital Markets Handbook 2026 examines that shift across the trade lifecycle....
Is the Matching Engine Still the Heart of the Exchange?
A panel at the A-Team Group’s recent ExchangeTech Summit London, titled Setting the matching engine at the heart of the exchange tech ecosystem – Next gen architecture, microservices and cloud migration strategies, positioned the matching engine as the centre of gravity in modern venue architecture. The discussion that followed steadily pulled that centre of gravity...
Institutions’ Data Governance Capabilities Strengthening Amid AI Adoption
Financial institutions are leading the way in strengthening their data governance capabilities as artificial intelligence reshapes the industry, research by the Enterprise Data Management Association (EDMA) found. The study, published in the international organisation’s annual Global Data Management Benchmark Report, found that financial organisations scored the highest, and beat all all other industries, in their...
Private-Market Investors Don’t Need to Wait for ‘Perfect’ AI Data, says JMAN
The shorter investment lifecycle of private-market investments has made it necessary for participants to access analytics and other data-led processes at speed. The obvious focus in achieving that has been on developing artificial intelligence applications. But piloting initiatives on evolving models can take time. Organisations want to test their applications to know they will work...
Broadridge Moves Agentic AI from Roadmap to Institutional Scale Product
Broadridge’s recent announcement that its agentic AI is live in production across more than 40 clients signals a move from capability disclosure to commercial commitment. The firm is now offering two consumption models: a managed services arrangement where Broadridge runs operations end-to-end with the agentic layer on top, and a standalone deployment of the same...
Where is the Edge When Everyone Has the Same Alt Data?
Has the institutional alternative data market reached a phase in which the easy sources of edge have closed? Datasets that once generated standalone alpha are widely distributed, the AI tooling layered on top of them is increasingly commoditised, and the differentiator has migrated to a less glamorous middle ground: validation, transformation, kill criteria, and the...