Market & Alt Data Insight Private Markets Data The latest content from across the platform
73 Strings’ Structured Data ‘By-Product’ Fuels Workflow Acceleration After Callisto Acquisition
French startup 73 Strings realised a couple of years ago that one of the by-products of its valuation platform was a trove of structured, standardised and consistently labelled data drawn from private markets. This, reasoned Chief Executive and Co-Founder Yann Magnan, was financial gold in a part of the financial sector that has traditionally been…
FactSet and Hamilton Lane Partner to Integrate Private Markets Data into Portfolio Analytics
FactSet and Hamilton Lane have announced a strategic partnership to integrate Hamilton Lane’s proprietary private markets data and benchmarks into FactSet’s portfolio analytics platform, enabling institutional investors to analyse public and private assets within a unified workflow. The integration will provide access to data covering more than 70,000 funds and 240,000 assets, alongside fund- and…
S&P Global Expands AI and Analytics Capabilities Across Private Markets
S&P Global has expanded the AI, valuation and analytics capabilities of its iLEVEL private markets platform, introducing new tools for portfolio monitoring, data management and investment workflows. The enhancements include a native iLEVEL Agent, AI-powered data ingestion and natural-language search, enabling investment teams to automate data-intensive processes and retrieve portfolio information more efficiently. An iLEVEL…
Dasseti Acquisition Provides New Private Markets ‘Chapter’ for Nasdaq
Nasdaq’s acquisition of Dasseti, a due diligence and monitoring platform, extends the exchange and data company’s interests in private markets and highlights the growing importance of the sector to capital markets investors. The deal, which was completed in September, will see the artificial intelligence-powered tools of Dasseti integrated into Nasdaq’s eVestment business, and rolled out across…
Why Agentic AI Is Shifting Attention Back to the Data Layer
The rapid improvement of large language models is changing the way financial institutions approach agentic AI. Model capability remains important, alongside the practical challenges of connecting AI to the right data, providing sufficient context, embedding agents into investment workflows and controlling what they can access and do. These issues featured prominently during a panel discussion…
Can Alternative Data Close the Credit Risk Visibility Gap?
Credit risk has traditionally been monitored through a familiar collection of fundamentals, ratings and market prices. But as private and public credit markets become more interconnected, investors are looking across a much wider range of data for signs that a borrower – or an entire sector – may be running into trouble. That search for…
Dakota Q&A: From Fund Raiser to Private Market Data Specialist
Two decades since its formation, Dakota has transformed its business from raising capital to providing private market participants with data and tech services. It’s history is one of nimble adaptation and being able to divine the growing needs of a booming yet often opaque corner of the financial sector. Company President Rob Robertson spoke to…
As AI Lowers the Bar for Alternative Data, Where Does the Edge Move Next?
Alternative data has spent much of the past decade moving from the margins of investment research towards the mainstream. Now, artificial intelligence is accelerating that process, making datasets easier to discover, evaluate, process and combine while allowing investment teams to tackle sources that would previously have required considerable engineering resources. But that creates a new…
Do Private Markets Have a Data Interoperability Problem?
Private markets generate large quantities of data around investors, funds and transactions. Yet much of that information still moves between asset managers, wealth platforms, custodians, administrators and other participants through PDFs, portals and other document-based processes. Information that already exists digitally can be embedded in a document, sent to another organisation, extracted and then entered…
Beyond the API: FactSet on Making Financial Data Ready for Agentic AI
The effectiveness of an AI agent ultimately depends on the quality, context and structure of the information it can access. For investment firms, that puts familiar challenges around data quality, provenance and integration firmly back on the agenda – while potentially changing what they expect from their data providers. “When you’re selling data, you’re not…