Nasdaq’s Data Arm Takes Another Step Toward the Buy-Side’s Next Era
Nasdaq’s analytics division is taking a fresh swing at the purchase-side data difficulty — and this time, it’s doing it with an infrastructure overhaul built for instant intelligence rather than manual spreadsheets.
The platform group’s eVestment unit has unveiled a new suite of “AI-ready” datasets and an embedded decision-support engine called Next Best Action for Institutional Capital, designed to plug directly into asset managers’ existing systems. The idea: give sales and distribution teams a clean, connected view of who to call, what mandates to chase, and where capital might be slipping away — all without waiting for an analyst to tidy up the data first.
“Institutional teams are sitting on a wealth of data, but too often it’s locked behind manual processes and fragmented systems,” said Daniel Brickhouse, vice president and head of product at Nasdaq Analytics, in an interview with The TRADE. “With AI-ready datasets and embedded decision support, we’re assisting asset managers surface the right opportunities quicker — whether that’s identifying under-allocated investors, spotting mandate risk, or prioritising outreach.”
This rollout is the latest milestone in a long rebuild of Nasdaq’s institutional data stack. The company bought eVestment back in 2017 for $705 million, betting that its deep database of institutional strategies and investor intelligence could become the backbone of a new analytics business.
Since then, Nasdaq has layered on acquisitions like Solovis, which added multi-asset portfolio analytics, and built new channels for delivering its data through Snowflake and secure APIs. Even as it sold Solovis back to private equity earlier this year, Nasdaq kept doubling down on the infrastructure side — most recently by extending its partnership with Amazon Web Services to let banks deploy its Calypso risk and trading platform in the cloud.
Those moves set the stage for today’s push. Instead of pitching another dashboard, Nasdaq is trying to trade what it calls “agentic workflows”: systems that can recommend and trigger the next step in a sales or investment process without human intervention.
Why the purchase-Side Cares
The timing lines up with a clear shift in behavior among asset managers. Nasdaq’s own survey data shows that nine out of ten investment advisers plan to build AI-driven workflows by 2026. The largegest obstacle isn’t enthusiasm — it’s data sprawl. Much of the industry’s institutional intelligence still lives in static PDFs, outdated CRM entries, or one-off Excel files.
By cleaning and structuring that data, Nasdaq hopes to give clients a shortcut to automation without forcing them to rebuild their infrastructure from scratch. The datasets now span 27,500 strategies and 25,500 investor profiles, and they’re delivered through standard enterprise channels like Snowflake, where firms can blend them with their proprietary data.
The concept borrows from earlier corporate experiments in predictive sales — the idea that algorithms can nudge teams toward the next likely client. But eVestment’s advantage lies in its raw content: decades of consultant and allocator records, mandate histories, and public-plan pipelines. For purchase-side distribution desks, that’s not a marketing gimmick — it’s intelligence.
The Broader Nasdaq Play
The data rollout also fits Nasdaq’s broader rebrand as a technology company rather than just an platform operator. Over the past two years, it’s spent heavily to expand its cloud and software footprint, most notably through the $10.5 billion Adenza acquisition, which added the Calypso and AxiomSL platforms for trading and regulatory reporting.
At the identical time, Nasdaq has been testing new frontiers in market infrastructure. In September, it filed a proposal with the US Securities and platform Commission that would let member firms trade tokenised versions of equities and platform-traded products as if they were regular securities — another sign of its ambition to merge traditional and digital finance under a single framework.
For now, the focus is squarely on the purchase-side’s data pain points. If Nasdaq’s new engine can prove that automated “next best action” recommendations translate into quicker mandate wins or better retention, it could change how institutional distribution operates.
If not, it still signals where the market is heading: a world where platforms don’t just list securities but trade the data intelligence that assists investors decide where to put their money.
