Machine-readable news platform provider RavenPack has granted access to its historical data to crowd researchers seeking alpha signals on CloudQuant’s online Python and JupyterLab-based tools. The initiative aims to support data scientists designing tools to improve financial modelling.
Data is the fuel that keeps modern financial institutions’ motors running but if that data can’t be trusted then the decisions made based upon it, or the uses to which its put, will be compromised. That’s especially important for data that’s fed into artificial intelligence models. If the data isn’t clean, accurate and complete, then...
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....
Buy AND Build: The Future of Capital Markets Technology London examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.
Welcome to the fourteenth edition of A-Team Group’s Regulatory Data Handbook. Supervisors increasingly expect firms to demonstrate which rules apply, which data supports each obligation, who owns the control and how exceptions are identified and resolved. Policies and implementation programmes must now be supported by records that can withstand regulatory scrutiny. This edition examines material...