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Financial Operations Has an Invisible Tax Problem. AI Is Starting to Fix It
By Neil Vernon, chief product officer at Gresham. The financial services industry has spent considerable energy debating whether AI is production-ready for regulated operations. That debate has been asking the wrong question. Readiness is not the constraint; targeting is. The real question is whether firms have correctly identified where AI can address costs that have…
NeoXam Agent Attaches Automative Functionality to Platform
NeoXam has launched NeoXam Agents, an agentic artificial intelligence platform for building and supervising artificial intelligence agents, a set of specialised agents in preview and an early-adopter programme launching in the third quarter. The innovation attaches digital agents directly to the company’s existing products across the back and middle offices of investment firms to utilise…
Closing the AI Gap: Why Financial Institutions Must Move Beyond Pilots to Enterprise-Scale Impact
By Ravi Sidhu, UK&I risk and compliance solutions at Dun & Bradstreet. AI enthusiasm across financial services is at an all-time high, but measurable enterprise-wide success remains elusive. While UK businesses are moving quickly in AI readiness, with 52 per cent already using third-party AI platforms or modern cloud-native infrastructure to deploy AI workloads at…
Agentic AI’s Data Quality Imperative: AI in Capital Markets Summit Review
Artificial intelligence agents are not only changing the way organisations deploy new technology, they are also throwing new challenges to data managers as the autonomous structures place new demands on their infrastructure. It’s not enough that AI needs good-quality data to generate and perform the most accurate and safest outputs; agents are also prompting a…
Data Now Front and Centre of Fixed-Income Trading, Bloomberg Forum is Told
As the operations of buy-side traders and their sell-side counterparts increase in complexity, their data needs have surged. Technology that has made it possible to compress the work they do into shorter time scales and with more effective outcomes, requires large volumes of information that is either generated by their own systems or has to…
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…