Transforming the trade lifecycle with pricing and reference data in the cloud

As financial institutions accelerate digital transformation, consistent access to pricing and reference data in the cloud is becoming critical for governance, agility and innovation, say LSEG Data & Analytics’ Kashif Akhtar and Simon Gauld

Across global markets, financial institutions are redesigning their data architectures to improve how they organise and use data to support trading, risk and post-trade functions. These activities are increasingly data-driven, yet the complexity and volume of market, pricing and reference data have surged in recent years. As new asset classes, regulatory requirements and analytics models proliferate, traditional on‑premises infrastructure is reaching its limits.

Kashif Akhtar, LSEG Data & Analytics

Firms are shifting their data infrastructures to the cloud to improve consistency and efficiency across their data ecosystems. Cloud-native platforms make it possible to deliver high-quality data to users and applications anywhere in the world, instantly and securely. According to a recent LSEG survey, 47% of financial institutions worldwide already use market and pricing data in the cloud, and 38% are using reference data this way – figures that continue to rise as digital transformation accelerates.

Data fragmentation and operational drag

Despite the progress, many firms remain constrained by legacy data environments that are siloed, inconsistent and costly to maintain. Different desks or regions may rely on their own versions of reference data, resulting in reconciliation breaks, and latency and governance issues. Onboarding new datasets or analytics tools can take months, requiring expensive infrastructure and slow manual processes.

Simon Gauld, LSEG Data & Analytics

These challenges are more than operational irritants – they directly impact business performance. Fragmented data architectures slow down time-to-market for new trading strategies, complicate regulatory reporting and undermine confidence in analytics outputs. As institutions pursue artificial intelligence-driven models and real‑time risk management, the inability to access harmonised data becomes a strategic constraint.

Cloud data’s role in modern trading

The move to the cloud is not simply about cost or convenience – it represents a structural shift in how data underpins every stage of the trade lifecycle. From pre-trade analytics and execution to post-trade processing and risk oversight, consistent access to trusted data allows firms to align decision-making across functions and geographies.

Cloud-based data platforms make this possible by providing a single, harmonised source of pricing and reference data that can be queried and integrated in real time.

By hosting these datasets directly within cloud environments such as Snowflake and Google BigQuery, institutions can combine them with other sources for analysis, modelling and risk management. This reduces friction between teams and enables data to flow seamlessly from trading to risk, compliance and finance functions.

47% of financial institutions worldwide already use market and pricing data in the cloud, and 38% are using reference data this way – figures that continue to rise as digital transformation accelerates

LSEG Data & Analytics’s cloud-based data service is delivering its high-quality pricing and reference data directly into clients’ preferred cloud platforms. Using Snowflake Private Listings, the service allows firms to share and access data securely across regions and cloud providers, lowering the cost and complexity of managing multiple data environments while improving performance and control.

Use cases across the trade lifecycle

In trading, consistent pricing data supports pre-trade analytics and valuation modelling. Risk teams use the same datasets to run stress tests and scenario analyses, ensuring alignment between front-office assumptions and enterprise risk reporting. Operations and finance functions can automate reconciliation and corporate actions processing using a single, authoritative source of reference data.

Because all data resides natively in the cloud, teams can collaborate globally without version conflicts or latency issues. Developers and data scientists can connect directly to the platform through secure application programming interfaces and cloud interfaces, integrating it with real-time feeds, tick history and machine‑readable news from LSEG’s broader data ecosystem.

From data delivery to data intelligence

LSEG Data & Analytics is continuing to develop its cloud-based data service to reflect how financial institutions now use information – not only to feed systems, but to generate insight.

Recent additions such as Change Tracking from Snowflake and new datasets, including corporate actions, are designed to strengthen governance and extend the range of data available for analysis. The emphasis is shifting from simply distributing data to helping firms manage and interpret it more effectively across cloud environments.

The broader vision is clear: to help financial institutions transform the way they access, manage and apply data across the trade lifecycle, building a foundation for innovation and resilience in a rapidly changing market landscape.

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