Data Management Insight AI, Data Science & Analytics The latest content from across the platform
Upcoming Webinar: The ROI of Data Trust: Quantifying the Business Value of Data Observability
Date: 8 July 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes 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…
The Business Conduct Risk and Data Challenge Behind AI Adoption
Poor data preparation for artificial intelligence deployments is exposing financial institutions to greater business conduct risks that could cost them as much as US$43 million per year, according to new research. An updated report by business conduct data provider RepRisk found that such AI-related incidents are on the rise as applications are rolled out at…
MCPs in Data Management: Bringing New Order to Private Markets
Financial institutions have begun deploying Model Context Protocols (MCPs) as they have expanded the use of artificial intelligence applications and agents. The technology developed by Anthropic is an open-source contextual layer that helps coordinate models and data, enabling AI applications to connect with a multitude of other platforms and processes. In the first of a…
EXL Integrates NVIDIA Foundation Model to Expand Proprietary Data Use
EXL has integrated the Build Your Own Transaction Foundation Model developer example from NVIDIA into its artificial intelligence and analytics offerings, enabling financial institutions to build and deploy transaction intelligence applications using their own data. The application uses a foundation model designed to analyse billions of transaction events, such as payments, transfers and behaviour signals….
Agentic AI, Data Readiness and Governance Shape AICMS London 2026
AI adoption in capital markets has entered a more exacting phase. The early cycle of pilots, productivity tools and isolated use cases is giving way to questions of operating model, governance, data architecture, control evidence and return on investment. A-Team Group’s AI in Capital Markets Summit London 2026 will examine that shift through a practical…
Immaturity of AI Shines Through in Report Highlighting Persistence of Age-Old Data Challenges
The relative novelty of artificial intelligence use within financial services has been highlighted in a global study of the technology’s adoption, with many data challenges remaining and blind spots in security still widespread. While the 2026 Global AI in Financial Services Report by the Cambridge Centre for Alternative Finance found firms were eager to integrate…
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….
Duco’s Post-Trade Agents Seen Substantially Reducing Reconciliation Times
Duco has launched an agentic operations platform for post-trade workflows.The platform relies on an engine that processes 20 billion transactions monthly for more than 200 clients, the financial services data automation provider said. Ten firms are using the autonomous agents in production, benefiting from a decrease in the time required to build a new reconciliation…
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…