Agentic AI in Financial Services: Nasdaq’s eVestment™ is Leading the Pack
For global asset managers, the era of AI pilots and POCs has officially passed. Today, agents are fundamentally reshaping the landscape, transforming workflows across the industry. This is not an incremental technical achievement. It is a profound strategic shift driving an unprecedented wave of productivity, efficiency and competitive advantage across the sector.
As autonomous, goal-oriented programs, agents are engineered to perform complex, multi-step business tasks with varying degrees of human feedback. For asset managers, this capability translates directly into agents that can, for example, generate comprehensive reports, autonomously analyze data and leverage multiple tools to compress the time between information, insight and action. The most advanced adopters are also using in-house data, combined with agentic intelligence, to track the big investment themes that matter to institutional investors, such as private markets, societal shifts, and AI and technology.
Executives expect ROI
Senior leaders have moved beyond the planning phase and are now demanding clear, quantifiable ROI, delivered in months, not years. The priority has shifted toward high-value strategies, bypassing endless cycles of AI experimentation. This executive mandate has also elevated speed-to-insight into a nonnegotiable source of business value.
Critical barriers to ROI success
As asset managers set to work deploying agents at scale, it’s common for them to face a handful of key challenges, centered primarily on data architecture, governance and control, including:
Creating a trusted data foundation: Agents are only as good as the data and context they are given. Many organizations struggle to unify structured, semi-structured and unstructured data, and to establish a consistent semantic layer that gives the data meaning and business context. Without this foundation, agents can’t operate with a complete, reliable understanding of the business and, as a result, the quality of their outputs is at risk.
Ensuring comprehensive governance and data privacy: In highly regulated industries such as financial markets, firms must guarantee that AI agents operate within strict access controls, established policy frameworks, audit requirements and data protection standards to safeguard sensitive information. Clear audit trails are particularly essential for regulatory compliance and oversight.
Reducing data movement and platform complexity across fragmented ecosystems: Agentic AI initiatives frequently stall when financial institutions rely on complex, disconnected architectures that force data to move across too many systems and make it difficult to seamlessly connect new AI solutions with legacy platforms, third-party tools and diverse enterprise data environments.
Enforcing observability and operational control: Organizations require detailed visibility into how AI agents retrieve data, make decisions and execute within core business processes.
Nasdaq eVestment: Leading agentic solution in institutional investing
Nasdaq eVestment provides the indispensable competitive intelligence required for asset managers to be discovered, researched and selected by the consultants and allocators controlling over $131 trillion in global assets.
In direct response to client demand, Nasdaq eVestment now delivers near real-time and in-depth institutional data and insights through a strong partnership with Snowflake and its secure, interoperable platform. As Dan Caron, VP Head of Enterprise Revenue at Nasdaq eVestment, says, “Nasdaq eVestment is trusted by the global institutional community for having the 'best data in the industry.' Its strategic partnership with Snowflake is driven by the fact that mutual clients demand the institutional data set to be AI ready and available directly within Snowflake.”
This robust foundation enables clients to access AI-ready data, integrate it seamlessly alongside their proprietary first-party data and apply diverse AI platforms on top, allowing agents to be set up "very quickly," says Caron.
Nasdaq’s AI data cloud strategy accelerates time-to-insight for asset managers by eliminating manual, time-consuming ETL processes and other complex data integration hurdles.
Nasdaq eVestment’s ‘Next Best Action for Institutional Capital’ agent
Nasdaq eVestment has been an early adopter of agents and has brought to market a "Next Best Action" agent that offers asset managers a data-driven methodology for evaluating investment opportunities with public pension plans, using its proprietary participant factor model. The agent assesses asset managers' strategies across multiple factors, including performance, risk management, incumbent relationships and alignment with institutional investors’ goals.
It’s intentionally designed to compress critical front-office workflows and provide immediate conversational intelligence. The agent leverages core capabilities within Snowflake's AI solution Snowflake Cortex AI and is instantly accessible on the Snowflake Marketplace. And its participant factor model provides transparency and consistency in identifying high-potential mandates, whether hiring a new manager or increasing an existing allocation.
The agent is also equipped with a semantic layer that adds business context and meaning to the raw data. This allows for faster solution deployment by reducing the need for manual data preparation and interpretation.
Key elements of Nasdaq’s agent that deliver efficiency include:
Proprietary scoring model: This model uses complex signals — including product and fund-level data, asset flows and consultant activity — to triage and prioritize opportunities, presenting clients with their "top opportunities." This initial phase alone yields significant efficiency gains.
Agentic workflow and contextual enrichment: The agent augments this raw scoring model with deep contextual intelligence by leveraging Snowflake Cortex Analyst and Cortex Search. This transformation moves the user experience from simply viewing a list of opportunities to complex sales preparation in just a few minutes. Users shift from asking a generic question like, "What are my opportunities?" to discovering granular, actionable details, such as who is the consultant, what they have said about me in the past six months, and how do I position my products.
Measurable impact
The agent’s immediate access to Snowflake Marketplace provides actionable, hyper-contextual insights for asset managers, delivering a "huge revenue unlock.” In fact, early adopters report 10x faster prospect identification and a 20-30% lift in win rates. This dramatic efficiency gain allows sales teams to expand their proactive coverage ratio by 2x to 3x using the same headcount, enabling them to capture substantially more revenue.
Early adopters report 10x faster prospect identification and a 20-30% lift in win rates.
Key aspects of Nasdaq eVestment’s infrastructure and partnership
The success of the Nasdaq eVestment agent is founded on a strategic infrastructure and partnership with Snowflake, intentionally designed to directly solve the governance, data quality and complexity challenges common at large financial institutions.
The partnership provides a number of benefits, including:
AI-ready data as the catalyst: Nasdaq eVestment has made its institutional data set AI ready by applying semantics and orchestration layers via Snowflake Intelligence. This delivers immediate value, allowing clients to prospect against the entire institutional market without the prerequisite, time-consuming cleanup of internal first-party data.
The strategic build vs. buy decision: The company focused on its core competencies — data quality and domain expertise — while leveraging the platform’s underlying capabilities. This choice makes it possible for them to continue rapidly innovating while adhering to stringent enterprise-grade requirements.
Robust governance and risk management: In this highly regulated industry, agent deployment demands strict frameworks for transparency, auditability and verifiable data to prevent hallucinations. Critical organizational practices include ensuring the early involvement of legal and security teams and maintaining reliable "kill switches" for autonomous agents.
The agent's capabilities depend heavily on Snowflake’s inherent governance and AI features: Cortex Search and Cortex Analyst process and analyze data; Document Processing prepares unstructured data for retrieval-augmented generation (RAG); and the Snowflake Marketplace securely shares Cortex Search indexes as tools with full governance and role-based access control (RBAC).
As William Schmidt, Product Manager, Nasdaq eVestment, says, “The guidance and partnership from the Snowflake team are essential, ensuring that data delivery and formatting meet the back-office requirements for effective pipeline integration, even as the front-office champions the commercial impact.”
Nasdaq eVestment’s future plans
The company’s future trajectory is unambiguous: to relentlessly compress and agentify more institutional workflows in the coming quarters.
The next major transition involves moving agents from being simple analysis tools to becoming autonomous "members of the team." Future agents will continuously monitor data and take proactive steps, for instance, automatically creating a sales opportunity in the CRM the moment a new mandate is detected. This fundamentally redefines how sales teams operate.
In the race for AI advantage, models are rapidly becoming commoditized. The true gold is in the quality of the trusted, domain-specific data used for training and context. Nasdaq eVestment’s AI ready foundation on Snowflake delivers immediate, tailored value that generic models simply can’t replicate.
Successfully entering the agentic era
The time for AI experimentation is definitively over and the eVestment team has embraced this reality, pushing the envelope with Cortex agents. For financial executives seeking to successfully lead their next phase of strategic growth, embracing agentic AI and leveraging domain-specific data on the Snowflake AI Data Cloud for Financial Services is the defining strategy to unlock significant, sustainable revenue growth.
Want to learn more? Read our latest blog about how Snowflake powers the agentic ecosystem in financial services.
Learn how to advance your trustworthy AI in financial services strategy at Snowflake Summit on June 1-4 in San Francisco.
