Unlocking Financial Markets: Understanding The Role of Data in a Digital Economy

Executive Letter

Data is the cornerstone of the modern digital economy, fueling product innovation across industries, from healthcare to entertainment to logistics and beyond. Companies are using real-time information, advanced analytics, and artificial intelligence to create new products, improve decisions, and operate at greater speed.

Nowhere is the influence of data more profound than in the financial industry, where information serves as the basis on which prices are formed, liquidity develops, risk is managed, and confidence is sustained. From price quotation and trade execution to rebalancing portfolios, every action across the trade lifecycle comprises an immense flow of data moving through models, trading systems, exchanges, and analytics platforms.

Today, the financial system stands at a new inflection point. The first major transformation moved markets from floor-based trading to electronic infrastructure. The next frontier is to move beyond digitization toward an always-on operating model defined by AI-enabled decision-making, on-chain infrastructure, immediate or near-immediate settlement, non-stop trading, and eventually even new forms of computation such as quantum computing.

These developments promise meaningful benefits: faster settlement, broader access, improved automation, new forms of programmability, and more efficient capital formation. But they also increase the system’s dependence on trusted, observable, and continuously available market data.

In a market that operates more continuously, across more venues, through more automated systems, the system’s dependence on trusted, observable, and continuously available market data only increases. In more autonomous workflows, there is no margin for ambiguity. AI models do not create truth. Smart contracts do not independently know fair value. Risk systems cannot govern what they cannot observe. The need for a shared source of truth becomes more important, not less – derived from data that is transparent, standardized, regulated, and auditable.

Yet even as the financial industry invests billions in other market data to generate even greater insight, the most essential data – the regulated, standardized information flowing from exchanges – remains one of the most cost-effective assets in the marketplace. The integrity of core exchange market data ensures prices reflect reality, liquidity remains deep, and confidence in the system endures. Put simply, global finance runs on the shared truth provided by trusted exchange data, a role that becomes even more important as markets grow more automated and decision-making occurs on a more autonomous basis.

While innovation throughout the data ecosystem continues to accelerate, attention must be paid to the relationship between these layers and the value each contributes to market participants.
It is important to distinguish between the foundational market data that enables price discovery and the many products, analytics, and insights built upon it. Understanding that relationship is essential to understanding how modern capital markets function and where value is created across the broader data ecosystem.

This white paper explores the value of exchange data as the foundation of that trust. It examines the role exchange data plays in supporting price discovery, transparency, risk management, and innovation across the broader financial ecosystem. The conclusion is clear: as markets evolve, preserving the integrity of transparent, regulated exchange data will remain essential to market resilience, investor confidence, and future innovation.

Jeff Kimsey

Global Head of Data Regulation, Nasdaq

Introduction

Today, organizations across industries are increasingly moving from digital workflows to data-driven and AI-enabled operating models. Healthcare organizations use data to improve patient outcomes and accelerate research. Logistics networks rely on realtime data to coordinate the movement of goods around the world. Manufacturers use data to optimize production and strengthen supply chain resilience. In retail, companies use real-time inventory, consumer behavior, and supply chain data to dynamically optimize pricing, personalize recommendations, and ensure products are available exactly  when and where customers want them. Across sectors, a common reality has emerged: the ability to generate, manage, and transform trusted data into actionable insight has become a fundamental source of competitive advantage.

In capital markets, exchange data plays a foundational role. It powers price discovery, liquidity formation, and real-time risk management. For market participants, transparent exchange data ensures fairness, accuracy, and confidence, supporting trades that reflect true market value and a level playing field.

Yet despite its centrality to sound market operations, the value of exchange data is often misunderstood and undervalued. Too often, it is viewed through the lens of cost alone, obscuring the role that exchange data plays as the infrastructure that enables price discovery, transparency, liquidity formation, and risk management. This perspective overlooks both the significant investment required to maintain trusted market data and the broader ecosystem of financial products, analytics, and innovation that depends upon it. As markets become increasingly automated, AI-enabled, and interconnected, understanding the true value of exchange data becomes more important, not less.

What You Will Find in This Paper

This paper comes at a moment when the financial system is approaching what may be one of the most significant infrastructure transformations in its history. The first major transition was from physical and floor-based markets to electronic markets. The next phase will be defined by always-on, machine-driven, and programmable financial infrastructure.

AI is reshaping how decisions are made, while on-chain infrastructure is redefining how assets are issued, transferred, and settled. At the same time, extended trading hours are expanding when markets operate, and advances in quantum computing may eventually transform how firms model risk, optimize portfolios, and secure financial systems. Together, these developments signal the emergence of a financial system that is faster, more automated, more distributed, and more continuous than anything that has come before.

This evolution makes the integrity of foundational market data even more essential. In always-on and AI-enabled environments, inaccurate data can be propagated and amplified instantly. In an on-chain environment, smart contracts and digital infrastructure still require trusted reference prices to connect code-based execution to real-world market value. The future financial system therefore depends not only on innovation at the edge, but on the reliability of the core data layer beneath it.

This paper draws on new research examining growth across the financial data ecosystem. While the industry has expanded significantly, encompassing both exchange data and a wide range of value added products developed by commercial providers (e.g., Bloomberg, LSEG), that growth has not been uniform across segments.

This paper will demystify the financial data stack between exchange market data, complementary market data, and alternative market data, which represent the three layers that form the foundation of modern financial markets. It explores evolving consumption patterns, the role of transparency in driving efficiency and trust, and the importance of continued investment in the integrity of exchange data.

We also highlight the substantial investments content providers make in trading systems, feed distribution, data centers, and technology upgrades required to support growing message volumes, performance demands, and cybersecurity needs. These investments improve the resilience, speed, and reliability of market infrastructure while being made against a backdrop of rising costs and inflationary pressures.

The question facing market participants today is not whether data is important. It is whether we believe that the future financial system will be built atop a foundation of transparent, standardized, and trusted market data. The transformation that is taking shape across the financial industry will redefine how capital flows, how liquidity builds, how decisions are made, and how trust is maintained. In this paper, we provide clear, fact-based evidence that exchange market data serves as mission critical infrastructure for modern capital markets, especially as they evolve toward always-on operations and are increasingly empowered by the automated and autonomous AI workflows. Our goal is to provide a clearer understanding of the foundational role that core exchange data plays in enabling the next generation of globally connected, always-on financial markets.

Section 1: The Role of Market Data in Capital Markets

Insights on the Data Economy

• Modern industries rely on continuous global data flows that support strategy, business decisions, and innovation.
• Always-on markets will rely on continuous availability of data and insights further accelerated by AI, for which trusted data is essential.
• Clean and centralized data infrastructure enables easier creation of new products and services, including raw data for analytics and reporting.
• The global digital infrastructure market is forecasted to grow at a CAGR of 27% from 2025 to 2034.  
• Financial market data spend surpassed $50 billion in 2025, driven by 6-8% growth between 2023 and 2025.

In addition, the importance of trusted market data extends beyond the artificial intelligence imperative. Markets are being modernized at pace amid a confluence of structural trends, from artificial intelligence to extended trading hours, accelerated settlement, and the gradual integration of on-chain infrastructure. Combined, these forces support the development of a financial system that is even more connected, continuous, and data dependent; simultaneously, they reinforce the critical need for data that is transparent, standardized, and continuously available.

The Lifecycle of a Trade

Nowhere is the value of data in capital markets more apparent than in the lifecycle of a trade. A single trade, from order placement to execution, clearing, and settlement, creates a cascade of data points that flow through this ecosystem. Understanding this lifecycle is essential to appreciating the value of exchange data and its role in market transparency, efficiency, and innovation.

Historically, markets operated around defined trading sessions, batch processes, and settlement cycles. That structure is changing. As trading hours expand, settlement cycles compress, and on-chain infrastructure enables more continuous transfer of value, the trade lifecycle is becoming less episodic and more continuous.

In an always-on environment, data does not simply support a point-in-time transaction. It continuously informs pricing, execution, risk management, margin, settlement, collateral movement, surveillance, and client reporting. AI-enabled systems may consume and act on that information with limited human intervention, while on-chain applications may depend on trusted market data to trigger automated contractual actions.

The lifecycle of a trade includes:

1. Order Initiation: A decision to buy or sell generates an order, typically placed through a broker or trading platform. This first step captures intent data, including asset type, quantity, and price conditions.
2. Order Routing: The order is transmitted to an exchange or alternative trading venue. Routing generates metadata about timing, direction, and venue selection, which itself has analytical value for understanding market dynamics.
3. Execution: The order (whether internalized at a broker, in a dark pool, or executed on exchange) interacts with other orders, contributing to price discovery. Execution data (trade price, size, and counterparty information) is disseminated in real time, enabling transparency and liquidity.

At each stage, over 2 billion quotes and over 150 million trades are produced and consumed by tens of venues, hundreds of vendors, thousands of trading firms, and millions of investors. While newer and more specialized data sets may expand the range of signals available to models, only exchange data provides the standardized outcomes required to label training data, evaluate model performance, and detect drift over time. Throughout that process, it is the exchange market data that ensures transparency, efficiency, and trust in financial markets. Without reliable data at each stage, markets would become opaque and fragmented, undermining confidence across market participants.

Market Data Usage to Fuel Growth

From a growth perspective, advances in storage, processing, and cloud distribution have made it easier than ever to unlock the value of data, enabling organizations to act on information at an unprecedented scale and speed. In parallel, several converging forces are further accelerating this trend, including:

• Competitive pressures: In a hyper-efficient market, data can help provide an informational edge, fueling competition.  Firms with access to marginally better market information can experience up to a 5-10% improvement in capital allocation efficiency, leading to higher returns on invested capital (ROIC) compared to peers. (source)
• Increasing speed of news and information: Markets are impacted continuously by a 24-hour news cycle and ubiquitous social media discourse.  The World Economic Forum compared sophisticated financial algorithms and traditional media analysis and found news and discussion of issues can influence a firm's value within milliseconds (source).
• Volatility and uncertainty: From geopolitical shocks to pandemics, institutions utilize high-quality data to model scenarios, manage risk, and maintain resilience. Over 70% of financial institutions surveyed reported increased reliance on high-quality data and digital infrastructure to manage risk and maintain operational continuity during the recent pandemic (source).
• Ease of use and convenience: New information and trading platforms striving to meet customer demand make data available to more participants, including retail investors, most of the time at no cost and with greater ease. Demonstrating this, retail investing flows rose ~50% from 2023 to early 2025 alone, with a significant portion of new investors entering the market due to the ease of onboarding, coupled with zero commission trading via mobile platforms. (source, source)

Notably, the rise of AI‑driven strategies is not displacing demand for exchange data across the trade lifecycle, but rather intensifying its role as a critical reference layer. As AI adoption accelerates, firms increasingly rely on authoritative market prices to test, retrain, and govern automated decision systems. This helps explain why market participant spending growth concentrates in derived products even as the underlying exchange data layer is also growing in global distribution demand.

Alongside these innovations in market data infrastructure, financial institutions, asset managers, and trading firms have dramatically expanded their consumption of market data over the past decade as strategies become increasingly complex and use cases multiply given technology, regulation and paradigm changes. That’s why the global digital infrastructure market, which includes data centers, 5G, fiber optics and wireless, is forecasted to grow at a CAGR of 27% from 2025 to 2034 (source). While the global data economy is growing, investment in financial market data worldwide has continued to climb, surpassing $50 billion for the first time in 2025 fueled by 6-8% growth between 2023 and 2025.

Section 2: Demystifying the Data Stack

Insights on Market Data

• The financial data ecosystem can be represented as a tiered pyramid with Core Exchange Market Data forming the base layer of the data stack and Complementary Market Data and Alternative Market Data forming higher layers of the stack.
• Fragmented data sources introduce bias risks for modeling.

Taxonomy and Strategic Value of Financial Data

The modern financial ecosystem relies on a wide range of data sources, each serves different purposes. Certain data sets provide clarity on what has happened, while others serve to provide context to help the interpretation of why events may have happened, whereas others may help users predict what might happen next.

Combined, the financial information that runs through the data stack can be thought of as a tiered pyramid. Each category of data, from the most foundational and transparent to the most fragmented and diverse, carries a different level of value. At the base is Core Exchange Market Data, the essential foundation of price discovery. Above this layer are Complementary Market Data and Alternative Market Data, which add context and competitive edge, but their value depends on the integrity of the foundational layer. Beyond the pyramid is Untapped financial data, including unused data with potential. Emerging data categories like digital assets do not find their place neatly into the data hierarchy at inception. Their appropriate place within the data pyramid becomes clear with further adoption and market evolution.

The Value of Core Exchange Market Data

• Enables fair and efficient price discovery through a trusted, authoritative view of the market.
• Supports regulatory compliance and best execution with standardized data aligned to frameworks such as Reg NMS and MiFID II.
• Provides transparency and market integrity through precise timestamping, auditability, and real-time surveillance capabilities.
• Reduces systemic risk and supports market stability by ensuring price discovery remains grounded in trusted information during periods of stress.
• Lowers compliance and operational costs through standardization, legal certainty, and streamlined reporting requirements.
• Serves as the gold-standard foundation for AI by providing the reliable, explainable, and auditable data needed for AI training, validation, and governance.

Core Exchange Market Data

Core Exchange Market Data is the most critical component for fair price discovery. Core Exchange Market Data¹ is standardized, precisely timestamped, and fully auditable. Its cost functions as an essential insurance against systemic risk, ensuring that, during periods of market stress, price discovery remains grounded in trusted, verifiable information and markets remain stable.
While this data serves as the shared foundation for transparency and confidence in markets, it is intentionally delivered through different data products designed to serve distinct market functions. Consolidated data supports public price discovery, while other exchange data products address acute needs across trading, risk management, and surveillance.

This data is aligned with global regulatory frameworks such as MiFID II and Reg NMS, providing the legal certainty and standardization required for best execution and reporting, which saves firms substantial costs. Sustainably funded through usage fees, its cost is minimal relative to the outsized economic value it enables.

Core Market Exchange Data also serves as the objective benchmark for AI training, validation, and governance, providing the explainability, auditability, and bias controls that regulators and firms increasingly require for automated decision making. Without this gold-standard baseline, AI-driven insights lose reliability and regulatory credibility. 

Complementary Market Data

Complementary Market Data generally relies on exchange market data and offers a more specific view tailored to the unique demands of each market participant. This data can encompass indices, funds, news, ratings, classification data, and corporate filings, amongst other specialized needs of the industry.

Unlike exchange data, Complementary Market Data is generally governed by agreements between participants rather than a centralized regulatory authority. This requires a high degree of diligence and specialized tools to combine and synthesize information from many disparate sources. When properly combined with Exchange Data, Complementary Market Data enhances insight and usability while remaining anchored to trusted market outcomes. 

Section 3: The Economics of the Market Data Ecosystem

Section 2 showed us that while complementary and alternative signals can enhance insight, their value ultimately depends on validation against observable market outcomes. That makes Core Exchange Market Data the critical foundation, providing the transparent, standards‑based record of bids, offers, and executions that anchors trust, fairness, and resilience in price discovery. It also creates a multiplier effect: this same gold‑source layer enables an expansive ecosystem of derived analytics and intellectual property products built on top of it. In this section, we move from concept to quantification, using new market‑sizing research to compare what firms spend on Exchange Market Data versus the revenue and investment that accrues in the higher layers of the data stack.

Despite the foundational role that exchange data plays as the foundational layer of the financial data ecosystem, this data accounts for only a minority of overall data revenues. The [vast] majority of industry spending is allocated towards higher-value segments of the data value chain such as Terminals, Research and Analytics, and Indices capture a disproportionately larger share of market data revenue (approximately 75%) compared to the Exchange Data itself (25%). 

Research: Foundational Exchange Data accounts for just 25% of the total market data revenue, while Terminal products capture the largest share at 32% 

Methodology and Market Segmentation Overview

To provide an objective, granular view of the financial data ecosystem, our analysis leverages market sizing research conducted by BCG Expand during September 2025. The methodology combined publicly reported revenue data with aggregated survey inputs from financial institutions across all major regions (Americas, EMEA, and Asia-Pacific) and business lines (Markets, Asset Management, Wealth Management).

This research defines the global market data ecosystem by three primary, related data tiers:

• Core Exchange Market Data: Regulated, transparent, pre- and post-trade data from lit exchanges.
• Complementary Market Data: High-growth intellectual property products built on top of the foundation, including indices, research, analytics, Standardized information (e.g., security master data, corporate actions, bond pricing) necessary for operations, valuation, and compliance.
• Alternative Market Data: Non-traditional data sets (e.g., social sentiment, satellite imagery).

This market sizing confirms that while Exchange Data remains the indispensable foundation for price discovery, the industry’s overall spending is overwhelmingly concentrated in Complementary Market Data and Alternative Market Data.

The Foundational Investment: Exchange Data in Equities

The equities market is uniquely dependent on transparent Exchange Data because it serves as the foundation for price discovery and market transparency. While Exchange Data represents roughly 25% of total equities market data revenue and roughly 36% of market data spending among cash equities users, its significance extends beyond its share of industry spending.  The prices formed and disseminated through exchange markets provide the reference point for trading decisions, investment products, analytical tools, and many of the value-added data services used throughout the financial ecosystem. Although revenue growth across major vendors and exchanges is increasingly driven by Complementary Data (now growing at near double digit rates), this innovation is enabled by the integrity of the core exchange data layer which therefore reinforces, rather than diminishes, the importance of maintaining the integrity, reliability, and transparency of core Exchange Data.

Consumption by Firm Segment and Use Case

Based on the business lines analyzed, the value derived from Exchange Data is seen to permeate two key, distinct consumer segments: wealth management and markets². While trading firms use Exchange Data to facilitate execution and manage risk, wealth managers rely on the same trusted information to value portfolios, meet regulatory requirements, and provide transparency to investors. The comparable usage across both segments demonstrates that Exchange Data is not solely a trading input—it is foundational infrastructure that supports both capital markets and the investors they serve.

BCG Expand Market Sizing research, estimates based on public reporting and BCG Expand data

The Investment Multiplier Effect in Market Data: Why Growth Accrues Above the Core Layer

Our most compelling finding is the stark divergence in the growth rates of fees between Exchange Data and the high-value products built from it. This reinforces the idea that the fees for core data layers have been stable, in some instances less than inflation (source), while an increase in fees has occurred in the value-add layers that use core data as a base. 

Over the five-year compound annual growth rate (CAGR) ending in 2025, the overall market data industry grew robustly at +7.3%. However, the drivers of this growth are heavily skewed toward curated, derived products. Market participants are directing their new spending toward sophisticated analytical and derivative products. Products like research and analytics, as well as indices (curated, processed, and packaged intellectual property derived directly from the underlying data) are experiencing double-digit annual growth, while the revenue generated by Exchange Data product itself is growing at a much more moderate +6.6% CAGR. 

* Growth expected from 2025 to 2030 based on GrandView Research

** CAGR from 2020-2025 BCG Expand Market Sizing research, estimates based on public reporting and BCG Expand data

This trend continues when examining the highly specialized Cash Equity segment. Here, the overall market growth is limited to +4.5% CAGR, but the Exchange Data revenue specifically within this specialized segment is only growing at +3.3% CAGR, reinforcing the disparity. In comparison, this level of growth trails the average inflation rate of approximately 4.5% per year. This demonstrates that the growth of the data ecosystem is predicated on curated, processed, and packaged intellectual property derived from the underlying data, rather than the raw Exchange Data stream. At Nasdaq, for example, revenue across the 2020-2025 timeframe for exchange market data has increased, primarily by welcoming new customers and upgrades from existing customers, rather than from fee increases.

While Exchange Data costs in the cash equity segment have remained relatively flat (+3.3% CAGR), message traffic has increased significantly. U.S. equities message traffic has more than doubled between 2019 and 2025 at a 19% CAGR. This implies a structural trend: data volumes appear to be increasing substantially faster than data revenues for exchanges, suggesting more value continues to be added while the cost remains low. This increase is primarily attributed to heightened market volatility and a significant rise in retail trading activity. And with extended trading hours on the way, message traffic is anticipated to continue to grow to unprecedented volumes. 

The Future Data Stack

As firms move toward more advanced use cases, including alpha generation, risk modeling, automated compliance, and real-time portfolio optimization, they will require two things:

1. A Stable, Verifiable Gold-Source: This will always be Exchange Data used to anchor all other insights, providing a common standard for truth, auditability, and explainability.
2. High-Growth Alternative Data: These unstructured and predictive data sets expand model capability but derive their economic value only when tested against transparent market prices.

The robust growth rate for Alternative Market Data (with a 54% increase expected from 2025-2030) reflects a surge in spending on integrating unstructured data, including social media sentiment, geolocation, and other Alternative Market Data sources (as discussed in Section 2).

The higher expected growth rate in Alternative Market Data of 54% confirms that market participants are directing new spend toward sophisticated, high-growth data sets.

Looking ahead, predictive modeling suggests this divergence in data spend will only accelerate as AI adoption matures, solidifying the role of Exchange Data as the universal "source of truth". As the financial system and society at large become increasingly dependent on artificial intelligence, the reliability of its outputs will be fundamentally determined by the quality of the data on which trading models are trained and validated. In this environment, a stable, verifiable, and standards‑based baseline of Exchange Data becomes essential to maintaining AI integrity. Without such a trusted foundation, the value of AI‑driven insights risks erosion, underscoring why Exchange Data will remain indispensable to both innovation and market confidence.

The conclusion is clear: the relatively low price paid for Exchange Data is not a barrier to innovation. The low, relatively stable cost of Exchange Data forms a transparent foundation that allows customers to build high-growth, high-value proprietary strategies, optimizing their overall Return on Data Asset (RODA). As such, the $3.3 billion spent annually on Exchange Data underpins the $50 billion market data industry.

Conclusion: It's Time to Reduce the Risk to Exchange Data

The financial system is entering a period of transformation that may prove as consequential as the move from floor-based trading to electronic markets. AI is changing how decisions are made. On-chain infrastructure is changing how value can move. Extended trading is changing when markets operate. Immediate settlement is changing the speed at which obligations must be funded, monitored, and completed. Future advances in quantum computing may change the scale and sophistication of financial modeling itself.

The benefits of Exchange Data should not be taken for granted. The long-term integrity of this critical data is increasingly tested by structural shifts in market architecture, including the expanding use of AI-driven trading and analytics amongst other advancements. While these innovations offer meaningful efficiency gains and enable new use cases, their long-term benefits depend on continued anchoring to verifiable, standards-based Exchange Data.

In an increasingly AI‑driven financial system, the reliability of automated decisions is inseparable from the quality of the data on which those systems are trained and evaluated. Exchange Data provides the

objective reference layer that helps ensure automated systems are grounded in transparent and verifiable market information.  Protecting and sustaining this gold‑source is therefore not only a market structure issue, but a prerequisite for unlocking $50 billion worth of value in capital markets.

Across every segment we examined, Exchange Data remains a stable, foundational input, even as adjacent data types command increasingly higher prices. While growth across the financial data ecosystem is increasingly driven by analytics, workflows, and other value-added offerings, those products continue to rely on the same underlying market information for pricing, valuation, benchmarking, and regulatory assurance. This research demonstrates that the value created throughout the broader financial data ecosystem remains closely linked to the quality and integrity of its exchange-based foundation.

At this inflection point, the market should be careful not to weaken the very layer that makes innovation possible. The future financial system will be faster, more automated, more distributed, and more continuous. That future will require many new technologies, but it will also require something more basic: trusted, standardized, observable market truth.  The choice facing market participants today is not between data and no data; it is between high-quality, standardized, competitive data and an opaque, fragmented system vulnerable to systemic risk.

At this inflection point, market participants should recognize that innovation and trusted market information are complementary, not competing, objectives. The future financial system will be faster, more automated, more distributed, and more continuous, but it will continue to depend on transparent price discovery, standardized reference prices, and reliable market signals. Exchange Data provides that foundation. Sustaining its integrity supports the fair, transparent, resilient, and innovative capital markets on which investors, issuers, and intermediaries rely.

¹ For the purposes of this paper, any reference to ‘Exchange Data’ should be understood as referring specifically to the ‘Core Exchange Market Data’ defined above.

² Outside of the two primary consumer segments, the Asset Management segment also accounts for 2% of exchange data allocation, servicing portfolio creation, risk modeling, and performance measurement.

³ Includes retail brokers as well as wealth management.