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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…
Clean Data Is Not Enough to Power AI
By Shai Popat, managing director, product and commercial strategy, financial information, SIX. Agentic AI projects are beginning to roll out across the financial industry. Many firms are testing AI’s feasibility by assigning it relatively simple tasks, such as summarising information or retrieving data and documents from internal databases. Two maxims are often cited when discussing…
LexisNexis Q&A: Ensuring Data Trust, From News to Governance
Since the 1970s, LexisNexis has been providing a variety of data services to financial institutions. Data Management Insight spoke to Danielle McCormick, vice president of product, Nexis Solutions – LexisNexis, to discuss how financial institutions are approaching AI, trusted data and the future of enterprise intelligence. Data Management Insight: Hello Danielle, when were LexisNexis’ data…
AI in Capital Markets Handbook 2026
AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied…