The Critical Role of Market Data Licensing in Modern Capital Markets

Introduction

Capital markets have evolved from a transaction-driven ecosystem into a data-driven ecosystem. Data is no longer merely a byproduct of trading; it drives the insights required to compete for liquidity in today’s markets, while serving as the foundation for essential activities throughout the financial ecosystem—from valuation and trading strategy implementation to risk assessment and margin calculations.

As passive investment strategies have grown as the driving force in today’s markets, competition for liquidity now hinges on the ability to consume data and derive actionable insights and market liquidity providers are utilizing data-driven signals to anticipate market behavior and exploit emerging opportunities.

Trading venues now compete for liquidity by providing data and information which informs the market and investors by driving liquidity intelligence attracting greater market participation and leveling the playing field for a broader diversity of market participants. As technology empowers more investors to consume vast quantities of data and form actionable insights, demand is driven for new types of data products that providers deeper insights with greater granularity.  

Technology has driven rapid changes in how data is consumed, creating more diverse distribution channels and transforming market data to a form of media where market events influence millions of investors, issuers, media entities, and regulatory agencies. Consequently, it is vital for data to be widely accessible and capable of flowing seamlessly across networks and applications. However, this widespread availability complicates tracking and accountability; effective governance of data rights thus continues to increasingly rely on static contractual agreements rather than dynamic technical controls, underscoring the critical importance of data licensing.

While technology has driven significant shifts in market structure, it has also driven significant changes in how data is consumed, used and distributed. The flexibility of data licensing frameworks to evolve with market structure is critical for the sustainability of our markets and competition. For exchanges, whose primary function is to facilitate price discovery, licensing ensures that the use of prices by investors and those participating in the price discovery process can be distinguished from those who redistribute or reference the prices for trading on alternative platforms or dark pools.

Data licensing plays a vital role in fostering competition, innovation, transparency, and broad market access, yet remains broadly misunderstood, and attempts to “simplify” commercial models, by reducing the number of licensing classifications, have created further ambiguity between data use and governing policies. The flexibility to accommodate a broad diversity of market use cases naturally results in a proliferation of licensing classifications. Standardizing these classifications while aligning with FRAND (Fair, Reasonable, and Non-Discriminatory) principles ensures ease of data governance and fairness. These principles-based frameworks have stood the test of time and proven to be more effective means of regulatory governance, while avoiding the disruption of competition and disruption.

What is Market Data Licensing?

Data licensing grants rights for specific uses of data, similar to how media is licensed for consumption. By differentiating between individual use and commercial redistribution, licensing frameworks ensure broad access to content while equitably distributing costs. Licensing fees proportional to individual consumption protect the value of the content and maintain competition across media sources, supporting a healthy, open marketplace.

Data, like media, enables transparency but relies on tools to interpret and transform raw information into actionable insights. These tools support market navigation, accountability, and trust. In the same way as media is licensed based on consumption, data licensing frameworks ensure fair access to information by applying FRAND principles to balance individual access and commercial redistribution.

These rights, enshrined in legal agreements, serve as the foundational framework governing commercial data relationships. These agreements define permissible usage patterns, access rights, and distribution parameters, ensuring that data utilization aligns with the provider’s intended use cases and strategic objectives.

Today’s licensing frameworks employ complex classification systems that segment usage rights based on factors such as user type, organizational scope, and specific use cases. This classification approach enables providers to maintain granular control over their data assets while promoting compliant usage through defined terms, conditions, and restrictions. By carefully structuring these agreements, providers can effectively manage data access and usage across their entire customer base, from individual users to enterprise-wide deployments, aligning usage with the value derived from the data and pricing appropriately.

Why Licensing is Necessary in Financial Markets

The capital markets landscape generates a continuous torrent of data, from microsecond-by-microsecond changes in order books to massive volumes of trade executions flowing through global exchanges. This market data serves as the foundation for nearly every aspect of financial operations, providing the essential inputs for trading decisions, risk calculations, compliance monitoring, and strategic planning.

Licensing frameworks ensure the sustainability of this data ecosystem by establishing fair compensation mechanisms for the valuable insights that market data provides. Organizations using data for real-time trading, risk management, or advanced analytics pay fees that reflect the value they derive from these information resources. This value-based licensing approach supports continued investment in data infrastructure and quality, while creating a fair marketplace where data providers can monetize their assets and data consumers can access the information they need for their business objectives.

Evolving Licensing Frameworks to Foster Innovation

Licensing frameworks must remain adaptable to accommodate new use cases as data consumption habits and demands evolve. The training of AI models is a prime example—if such uses are not explicitly catered for in licensing models, it risks undermining AI’s ability to provide equitable access to market intelligence for organizations of all sizes.

At its core, market data licensing serves as a cost-allocation mechanism that aligns fees with the value participants derive from the data. This model enables flexible frameworks where users pay based on their specific usage patterns and business needs, ensuring smaller firms can access essential market data without bearing the same costs as large institutions . For instance, a high-frequency trading firm consuming real-time data pays differently than a research firm using delayed data for analysis, or a small investment advisor may pay significantly less for delayed data or limited real-time access compared to a global bank consuming vast amounts of real-time data across multiple asset classes.

A one-size-fits-all licensing policy would threaten this delicate equilibrium, creating barriers to entry or leading to unsustainably low prices that degrade data quality. The current nuanced licensing framework recognizes that different market participants derive different values from data and use it in varying ways.

Commercial Licensing Policy Limitations

Market data providers have also played a role in limiting access to data by classifying new types of distribution as redistributors. Nearly a decade after extranets were created, exchanges began treating them as network providers and direct connectivity flourished. Earlier terminal providers enabled API access to data through the desktop eliminating the distinction of display terminals. User IDs became the proxy for devices but were later tokenized so that a User ID could be accessed on-demand rather than dedicated to each user. Contention access then became an issue where entitlement systems would need to kick a user out of the system before allowing another in to avoid exceeding a fixed number of user licenses. Then came caching, which does this at the edge of the enterprise system’s network to share access credentials to external sources of data for a fixed amount of API calls to minimize the cost of data re-use. More recently, Non-display use of market data has created new challenges for data providers to effectively govern and manage data use.

Policymakers and the Risks of Overregulation

As markets have become more fragmented requiring a greater diversity of sources of liquidity and data, market data costs have become a source of controversy and focal point of regulatory scrutiny, with authorities worldwide examining pricing structures to ensure fairness. While regulatory oversight is essential, the complexity of market data ecosystems requires careful consideration to avoid unintended consequences and a principles-based approach.

Blunt price controls or excessive regulatory constraints inadvertently disrupt competition and the evolution of the capital markets ecosystem. The sophistication of capital markets create barriers to entry by disrupting flexible pricing models and hampering the competitive environment it seeks to create. Smaller firms may struggle to navigate burdensome regulatory requirements, while larger institutions could absorb additional compliance costs. This dynamic could lead to market consolidation, reducing diversity and stifling innovation.

Rather than relying on blunt price controls that stifle competition and undermine free-market principles, fair, reasonable, and non-discriminatory (FRAND) approaches to licensing— applied through regulatory oversight —balance accessibility with commercial value. This ensures that individuals can access media affordably, while redistributors pay royalties that reflect their usage and commercial impact.

A principles-based approach to data licensing regulation – anchored in FRAND principles – ensures that markets can evolve at an accelerating pace while maintaining fairness and transparency. By fostering an environment where both traditional and emerging applications of data are supported, regulatory frameworks can strike a balance between encouraging innovation and enabling competition.

Vision for the Path Forward

The purpose of market data licensing supports market structure evolution, enables innovation, and ensures transparency and broad data availability. As regulatory scrutiny intensifies, the industry must demonstrate how licensing frameworks coupled with FRAND principles achieve a better outcome that supports regulatory objectives while avoiding damage to competition.

Rather than narrow the scope of license types to “simplify” pricing models, we must accommodate a growing diversity of use cases which align to the needs of investors and broad access to markets. In turn this broad participation will drive liquidity and price quality by representing a greater diversity of buy and sell interests.