The conversation around cloud adoption in financial markets has fundamentally changed. The era of tentative migration and justifying projects based on CAPEX vs. OPEX is over. As a new report from LSEG, “Cloud Strategies in Financial Services,” confirms, the cloud is now a strategic default. But this maturity brings a new, more complex set of challenges. The industry has moved beyond the ‘why’ and is now deep in the trenches of ‘how’ – how to achieve the performance required by the front office, how to measure a return on investment that goes beyond cost-cutting, and how to build a genuine competitive advantage.
In a recent conversation with TradingTech Insight, Kristin Hochstein, LSEG’s Global Head of Pricing & Reference Services, provided an on-the-ground perspective that brings the report’s data to life. The key takeaway is clear: the next phase of the cloud journey is less about infrastructure and more about empowering firms to innovate with data at scale, on their own terms.
Solving the Front-Office Performance Challenge
For any trading technology professional, the report’s finding that performance remains a key challenge is hardly surprising. System lag (36%) and scalability (37%) were cited as top concerns for intra-day data, with real-time data facing similar hurdles. While the public cloud has proven its worth for historical analysis, achieving the deterministic, low-latency performance required for real-time trading remains the final frontier.
“It’s crucial to differentiate between the performance requirements for different data types,” points out Hochstein. “For real-time, streaming data, achieving deterministic, low-latency performance in the cloud remains a significant challenge. In contrast, for static datasets like reference data or tick history, the cloud’s ability to provide massive scale and on-demand availability is a proven success.”
However, the gap is closing. Hochstein emphasises that both cloud service providers (CSPs) and data providers like LSEG are actively engineering solutions. The strategy is twofold. First, reduce the physical distance to data by moving resources closer to end-users to minimise latency. Second, optimise the technology stack for cloud-native environments. “Apache Parquet is key,” Hochstein notes. “Clients are excited about it. They want that greater efficiency. We’re also increasingly looking at Iceberg for larger, dynamic datasets. Those two formats go hand-in-hand with the cloud.”
The New ROI: It’s About Empowerment, Not Just Efficiency
One of the most telling strategic shifts revealed in the report is the evolution of how firms measure success. The top indicators for ROI are no longer about cost reduction. Instead, firms prioritise flexible capacity/scalability (51%) and revenue growth (47%).
This is a move from a defensive, cost-saving posture to an offensive, value-creating one. Hochstein distils this new mindset with a powerful quote from a client advisory forum: “Just give me everything, how I want it, when I want it.”
This is the new definition of ROI. It’s the freedom to experiment, to scale, and to access vast datasets without the traditional friction of procurement and provisioning. “Cloud scalability has enabled us to make over 100 trillion rows of data available to clients without them needing to bear the infrastructure burden,” notes Hochstein. “While we manage the cost of storing the data at scale, clients only pay for the queries they actually run. This pay-per-use model gives them the freedom to explore vast datasets and innovate without the traditional upfront investment, which is a massive competitive advantage.”
With this massive scale-on-demand, firms can move beyond operational efficiency – using the same data more cheaply – to generating new insights from a much larger pool of information.
From Consumers to Creators: The Strategic Shift to PaaS
This demand for greater control is directly reflected in a technological trend identified by the report: the move from Software as a Service (SaaS) to Platform as a Service (PaaS). This signals that firms are moving beyond consuming off-the-shelf applications and are increasingly focused on building their own proprietary solutions.
Hochstein explains this evolution with a food analogy. “We’ve moved from a SaaS model, which is like ordering from a menu, to a bulk ‘all-you-can-eat’ approach. The current evolution, enabled by cloud platforms, is the essence of the PaaS model: it’s like cooking in the kitchen. We provide the raw, high-quality ingredients – the data – and the high-performance appliances – the cloud tools. The ability for clients to write their own queries gives them the control to create their own unique recipes: their own alpha-generating intellectual property.”
Fuelling the AI Engine with Trusted Data
One primary driver for the next wave of cloud-native development is Artificial Intelligence. The report finds that 91% of firms are using or plan to use cloud services to develop AI and machine learning capabilities. But as the old adage warns, ‘garbage in, garbage out.’
For Hochstein, this puts the focus squarely on the data itself. “Clients are demanding more content to fuel their AI initiatives – deeper history, greater diversity, and cleaner tick data – but above all, they require data they can trust. This creates a dual role for AI. Internally, we use AI to enhance our own data quality to meet that high standard. We are also cautiously exploring how AI can help fill data gaps, though any such use would require clear disclaimers to protect the trust we’ve built on our structured sourcing and curation rules.”
The cloud makes it possible to deliver the petabyte-scale historical datasets needed to train effective models. But scale is not enough. The data must be clean, reliable, and trusted, a core value proposition for established providers. This combination of trusted data and scalable cloud compute is the foundation upon which the industry’s AI ambitions will be built, says Hochstein.
Ultimately, the LSEG report and Hochstein’s insights paint a picture of an industry at an inflection point. The technical and financial hurdles to cloud adoption have been largely overcome. The new challenge is a strategic one. As Hochstein concludes, the opportunity is to take the age-old framework of ‘better, faster, cheaper’ to the next level.
“It’s about insights,” she says, “”and it’s getting those insights faster than your competitor. In the cloud’s next chapter, competitive advantage will not come from simply being on the cloud, but from how effectively and creatively you use the data and tools within it to out-think the market.”
Discover more insights by accessing LSEG’s full report: ‘Cloud Strategies in Financial Services: Turning today’s challenges into tomorrow’s opportunities’
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