- Nasdaq leverages AWS to scale AI across its enterprise.
- The 'Intelligence Layer' unifies fragmented data from diverse fintech products.
- Emphasis on data quality, governance, and explainability for regulatory compliance.
- AI adoption is a strategic imperative; inaction carries significant opportunity cost.
In a rapidly evolving financial landscape, Nasdaq is taking a bold leap forward, strategically operationalizing AI across its vast enterprise and critical trade lifecycle. At the recent AWS FSI NYC 2026 conference, Mark Murphy, a key figure at Nasdaq, shed light on their comprehensive approach, highlighting a 20-year journey with AWS that culminates in a sophisticated 'intelligence layer' designed to unify data and enable next-generation AI workflows.
Nasdaq's commitment to AI is deeply rooted, extending beyond recent trends. Murphy emphasized that the organization has been building robust data platforms, semantic layers, and data models for decades, laying the groundwork for the current AI framework. This foundational work is crucial for their diverse portfolio of fintech products, including Verafin (anti-financial crime), Axiom XL (regulatory reporting), market surveillance tools, and Calypso (capital markets technology), which collectively serve thousands of banks, regulatory bodies, and exchanges globally.
The core of Nasdaq's strategy is the 'intelligence layer,' a unified data platform that transcends individual product silos. This layer is designed to address the challenge of fragmented data, ensuring high data quality, lineage, and enterprise-level governance. Murphy underscored the critical need for explainability in AI workflows, particularly when facing regulatory scrutiny. "Imagine a scenario where a regulator walks in... and they're talking to a human... the human will need to go and pull that data and be able to explain what happened," he stated, highlighting that robust architecture for explainability must be a proactive plan, not an afterthought.
Scalable deployment, trust, and the ability to train models on complete, wholesome data are paramount. Nasdaq's intelligence layer facilitates this by ingesting data from various sources, including non-native Nasdaq applications, providing richer context for AI models. This comprehensive approach not only enhances efficiency and enables new product development but also addresses the significant 'opportunity cost' of inaction in AI. Murphy warned that organizations failing to engage with AI risk being disrupted, positioning Nasdaq and its clients to move proactively rather than defensively.
Looking ahead, Nasdaq is excited about the potential of collective intelligence, where anonymized data can provide peer-group insights, helping clients identify workflow inefficiencies and improve performance. The platform also prioritizes client choice, offering interfaces, APIs, and contextual layers that enable partners and clients to build their own digital workers or leverage Nasdaq's agents, all within a secure and governed framework. This strategic vision, built on a strong partnership with AWS, aims to unlock unprecedented value and optionality for the global financial community.
“Pilots are great. We value them. We invest in them. We do them. But you have to accept that a pilot is a long way from moving to production at scale.”
