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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…
Daloopa Opens its AI Excel Agent Scout to General Use
Daloopa has made its artificial intelligence-powered financial modelling agent, Scout, generally available to clients. Scout enables analysts to build and update financial models directly in Excel using plain-language commands. Models created by the software draw from a structured database containing financial records for more than 6,000 global public companies. Thomas Li, Chief Executive at Daloopa,…
New CEO Appointed at Hexaware
Hexaware Technologies has appointed Vivek Jetley as CEO Designate to assume the CEO role at the IT services company on October 28. Jetley worked at EXL for 20 years, serving as partner at Inductis before its 2006 acquisition and holding leadership roles including president of analytics, insurance, healthcare and life sciences businesses. Jetley replaces outgoing…
SimCorp New Appointments Charged with Advancing Portfolio Management Platform
SimCorp has named Gareth Morris as Head of Portfolio Management and Trading, charged with leading development of the company’s SimCorp One’s portfolio management and trading capabilities. Morris, who previously worked on BlackRock’s Aladdin business for 16 years, will be joined by Kate Ryan, who was appointed Head of Product Design to drive the design system…
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…
15 Software and Data Vendors Solving Valuation, Integration and Reporting in Alternative Investments
The secular shift towards private markets has transformed alternative asset allocations from an institutional tactical sleeve into a core portfolio driver. Yet behind this expansion lies a stubborn operational bottleneck: alternative asset data remains inherently unstructured, fragmented and delayed. Unlike public equities, where standardised data feeds integrate seamlessly into order management systems, private market data…