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Semantic Frameworks Slow to Gain Traction Despite Criticality to Data Democratisation: Webinar Review
Semantic layers have become critical to financial institutions as they have expanded the use of artificial intelligence agents and widened staff access to them. The sophisticated interfaces give non-technical users the ability to guide agents to interact with their firms’ data and build efficient workflows. And yet, few organisations have really got their teeth into…
Data Management Summit NYC 2026 Ready to Examine Rapidly Transforming Industry
Final preparations are being made for A-Team Group’s 16th annual Data Management Summit NYC, which will bring leaders and experts from around the world to take a deep dive into the drivers, themes and trends that are shaping the data industry for financial institutions. Over a full day of keynote addresses and expert panel discussions,…
Finbourne Puts Even More Humans in the Loop to Build Client Confidence and Business
In an age when many firms are handing over ever more functions to artificial intelligence, Finbourne Technology is going all-out with investment in human engineers to take the company’s investment management data and technology capabilities to its customers. Finbourne has launched the Forward Deployment Engineering (FDE) programme in which it created a team of 30…
Mid-Tier Banks Benefiting from Integrated Data Overlay as Tech Demands Deepen, White Paper States
Integrated data overlays are offering mid-tier banks the opportunity to transform their data infrastructures without having to undergo disruptive and potentially expensive replacement projects. By creating a dynamic enterprise-wide data layer, organisations are able to knit together their data, no matter how fragmented, in real time and deliver a single source of truth for business…
The Integrated Data Overlay Approach to Solving Banks’ Data Challenges
Banks are under intense pressure from a variety of quickly evolving trends. Clients want more from them; market volatility is challenging their trading strategies; and regulator scrutiny is deepening. In response, regional banks and large banking organizations (LBOs) are offering more products to clients and promising ever-more automated access to a greater array of asset…
Rush to Build AI into Risk Models Creating Dangerous Capability ‘Gaps’
Asset managers may be exposing themselves to operational vulnerabilities as they rapidly integrate artificial intelligence and agents into their risk management systems, often without first ensuring trust in the data that will feed the models. A survey found that three-quarters of 178 senior investment leaders questioned said they expect the pace of AI and agents…
Data Quality Meaning and Importance Transformed by AI: DMS NYC Preview
The data management space has been transformed by artificial intelligence into one that not only seeks to prise maximum value from institutions’ data but also spends almost as much resource ensuring the quality of that information. Without optimised data, the AI and agentic tools to which it is deployed will churn out sub-optimal results. It’s…
Recorded Webinar: Building a Semantic Layer for Your Enterprise Data Estate
The democratisation of data has encouraged engineers to think about how to make their data estates more accessible and useable for non-technical business end-users. Translating intention into data action requires careful configuration that enables consumers to mine insight, analytics and value without having to use precise technical terminology. Data engineers achieve this through semantic layers,…
CDOs Play Increasingly Vital Role in Driving and Safeguarding AI Transformation: DMS NYC Preview
Modern chief data officers (CDOs) – and, more recently, chief data and analytics officers (CDAOs) – have an unenviable task. They are the gatekeepers of their organisation’s chief asset; its digital information. In the age of artificial intelligence, the importance of their role has been elevated and made more complex as the risks posed by…
Taming Data Complexity Through Semantic Layers: Webinar Preview
The complex data needs of modern financial institutions requires a level of technical mastery that is beyond the talents of most members of their workforces. Artificial intelligence and agentic automation, in particular, have hastened that evolution to such a degree that without such mastery across the enterprise, organisations leave themselves competitively vulnerable. The solution to…