Data redistribution model

Data redistribution

LSEG partners with organisations to deliver high-quality, compliant, and scalable market data solutions to their downstream customers. Our proven redistribution model helps firms innovate faster, reduce complexity, and integrate trusted data into powerful client-facing platforms and analytics. 

Overview

Firms increasingly rely on high-quality, compliant, and reliable data to build superior products, enhance client outcomes, and meet regulatory expectations. Yet the complexity of sourcing, managing, and distributing data at scale continues to grow. LSEG’s flexible and scalable data redistribution model helps firms deliver complete data enabled solutions by combining their own capabilities with worldclass market data for their end clients.

Whether you’re powering customer experiences or enabling solutions, our trusted data – backed by deep expertise in licensing and governance – gives you the confidence to scale securely and cost-effectively, at your own pace.

Our approach

LSEG supports redistribution of Real-Time, Pricing, Reference and Tick History data, alongside Machine Readable News, and other content globally. We help clients deliver complete solutions to their downstream customers by providing.

How we define data redistribution

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When LSEG licenses data for a firm’s internal use, this is data distribution. When that firm delivers the same data to its customers, it becomes data redistribution – an extended chain from LSEG, to the firm, to downstream users. Redistribution applies whether firms deliver raw market data or incorporate it into analytics, dashboards, AI uses, or client-facing outputs.

Derived data is the output that results when firms transform vendor-supplied data through analytics or by combining multiple datasets. If the output is unrecognisable, non-reversible, and cannot be traced back to the original content without exceptional effort, it qualifies as derived data. Even when outputs are derived, licensing requirements still apply – ensuring compliance across the redistribution chain.

In practice

Data redistribution is well-established across financial services. A selection of use cases LSEG supports include:

Fund administration

Support accurate Net Asset Value calculations, reconciliations and reporting with consistent, high quality data across asset classes.

Treasury management

Enable effective liquidity, cash and collateral management using timely market data and transparent pricing.

Wealth management & advisory

Deliver trusted insights to support portfolio construction, client reporting and long‑term investment advice.

Portfolio valuation & management

Maintain a consistent view of portfolios with reliable valuation, analytics and performance measurement.

Risk management & reporting

Identify, measure and report risk exposures with confidence across portfolios, instruments and market conditions.

Quantitative analytics

Power advanced models and strategies using granular data, robust analytics and historical depth.

Compliance, regulatory reporting & market surveillance

Support regulatory obligations and market integrity with transparent data, auditability and surveillance capabilities.

Instrument pricing

Access independent, trusted pricing to support valuation, trading, risk and regulatory requirements.

Trusted data, designed for redistribution

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Market data may be integrated, for example, into treasury platforms to assess exposures or hedging costs, or into wealth management portals delivering portfolio analytics and performance reporting.

Today, the landscape is evolving rapidly, especially in the increasing use of data for AI usage. FinTechs, RegTechs, banks and asset managers are building new digital platforms and analytics environments that rely on high-quality Real Time, Pricing and Reference data, Machine Readable News, Tick History data etc, to derive deeper insights and enable better decision-making – all set within redistribution frameworks governing how data can be used, transformed, and shared.

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