As financial institutions move more of their data workflows into the cloud, LSEG Data & Analytics argues that governance matters more than ever. The shift promises easier access and faster analytics. Without controls built in from the start, however, firms risk swapping old inefficiencies for new ones.
According to LSEG Data & Analytics, firms must now show clear control over how data is accessed, used, monitored and protected. They must also meet growing expectations around data sovereignty, operational resilience, auditability and regulatory reporting. Cloud architecture therefore cannot be judged on scale or flexibility alone. The real test is whether it creates a trusted operating model.
That distinction matters because accessibility without control breeds complexity. As more teams consume data, more workflows rely on automated access and new analytical use cases emerge quickly, a loose governance model becomes harder to manage. For pricing and reference data, which underpin trading, portfolio management, risk, compliance, operations and reporting, the consequences of getting this wrong are significant.
Historically, governance was often applied after data had been delivered, moved or transformed. LSEG Data & Analytics notes that this approach struggles in distributed environments where data flows across many platforms and teams. Security, lineage, access management and operational monitoring need to be foundational, not bolted on later.
Crucially, moving to the cloud does not automatically make governance simpler. If firms recreate file-based delivery, duplicated storage and fragmented transformation processes in cloud environments, they carry legacy control problems with them. Data may still need reconciling across systems, access may still be handled inconsistently and lineage may still depend on manual documentation. The outcome, as LSEG Data & Analytics puts it, can be cloud infrastructure without cloud advantage.
This is where compliance by design comes in. The approach treats control as a core part of architecture, requiring firms to know where data resides, how it is accessed, how metadata is handled and how services stay resilient during disruption.
LSEG Data & Analytics points to its DataScope Warehouse as an example of this model. The solution offers direct cloud access to pricing and reference data, which can be queried using SQL within platforms such as Snowflake and Google BigQuery, with Databricks availability coming soon. By reducing unnecessary file movement, staging and duplicated infrastructure, direct query models cut the number of handoffs where controls, lineage and access logic could break down.
Strong governance should not make data harder to use, however. The challenge is to enable analytics, reporting and AI without slowing them down, bringing trusted data closer to where work happens while keeping permissions, lineage and usage clear.
Resilience is also central. LSEG Data & Analytics stresses that resilience goes beyond uptime to include the ability to maintain control, explain data use and keep critical workflows running as decision windows shrink and regulatory expectations evolve.
Ultimately, compliance by design turns cloud-native architecture into a strategic control point. The firms that succeed, LSEG Data & Analytics concludes, will treat compliance not as a brake on innovation but as the condition that makes innovation safe to scale.
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