Plenty of banks have spent the last several years migrating pricing and reference data into the cloud, chasing flexibility and scale. According to LSEG Data & Analytics, a lot of them accomplished something narrower than they think: they relocated infrastructure without actually fixing how they govern that data.
The core problem LSEG points to is simple enough to state and genuinely hard to solve. If a firm’s cloud environment still relies on file-based delivery, duplicated storage and fragmented transformation steps, the cloud hasn’t removed old control problems at all, it’s just carried them somewhere new. Teams still have to reconcile data across different environments. Access controls still vary inconsistently from team to team. Lineage tracking still depends on someone manually documenting where a number actually came from. None of that disappears just because the infrastructure runs somewhere else.
That matters especially for pricing and reference data, since it feeds directly into trading, portfolio management, risk, compliance and regulatory reporting all at once. When more teams pull from the same data, when more workflows run on automated access, and when new analytical use cases spin up constantly, a missing governance model turns flexibility into a genuine liability rather than an advantage.
LSEG‘s answer is building control directly into the architecture instead of bolting it on after data has already moved. Its DataScope Warehouse lets customers query pricing and reference data directly within Snowflake and Google BigQuery using SQL, with Databricks support coming soon. The logic here is straightforward: every time a system stages, duplicates or shuffles data between platforms, that’s another point where access rules and lineage tracking can quietly break down. Querying data where it already sits, rather than moving it around first, cuts out a lot of those failure points before they happen.
Strong governance shouldn’t slow teams down, though, and LSEG frames this as additive rather than restrictive. Firms actually need data that’s easier to query and integrate while still carrying clear permissions and traceable lineage underneath it. Resilience factors into that equation too, not just whether systems stay online, but whether a firm can actually explain how people use its data and keep critical workflows running when something goes wrong.
The broader point LSEG makes extends beyond compliance checkboxes. Firms that treat governance as foundational, rather than adding it on after the fact, end up better positioned to scale AI and analytics work safely, instead of discovering the gaps only after something breaks.
