Valcon delivers Databricks projects in financial services sector

A recognized Databricks partner across Europe, Valcon has an established track record of delivering Databricks implementations for clients in the financial services sector. The spotlight on three recent projects that helped financial institutions transform data governance from an administrative burden into a strategic advantage.

Databricks is a cloud-based workspace that brings together data storage, data engineering, and AI capabilities into a single system. It introduces a ‘data lakehouse’ architecture, which blends the low cost and flexibility of a raw data lake with the organized, fast querying features of a traditional database.

Companies choose Databricks because it helps break down data silos while enabling data scientists, engineers, and business analysts to collaborate more effectively. Organizations use the platform to unify and clean complex datasets, reduce infrastructure costs, and develop advanced AI models that support faster, more informed decision-making.

Tackling financial crime and fragmented workspaces

One of Valcon’s latest projects in the domain addressed the complex data infrastructure of a major bank managing its financial crime data landscape. The institution operated across 13 separate Databricks workspaces and one Fabric workspace, each maintaining independent access policies.

With more than 4,000 permissions requiring manual synchronization, governance was becoming increasingly difficult to manage, while files were routinely duplicated up to 12 times across the enterprise data lakehouse. This resulted in significant inefficiencies.

Valcon resolved these inefficiencies by implementing Databricks Unity Catalog. By deploying automated workspace management tools and designing a governance framework specifically for AI models, Valcon established a single, secure approach to access management. This shift introduced automated lineage across all data assets, which drastically cut down the time required by the platform team and significantly reduced cloud storage and compute costs.

Optimizing risk analytics and cutting cloud expenses

Valcon delivered a similar modernization for another banking client whose largest risk analytics platform relied on outdated legacy code. The platform failed to utilize modern data governance practices, widening the gap between bank operations and current market standards. Valcon conducted a one-month proof of concept followed by a six-month implementation phase to bridge this divide.

The project delivered an immediate 24% reduction in monthly public cloud costs, unlocking significant savings.

By shifting from a file-based workflow to Unity Catalog, Valcon introduced technical data lineage to ensure compliance with stringent banking standards. The team identified 10 distinct improvement areas spanning storage strategy and performance, sparking a cultural shift toward reducing technical debt.

Standardizing infrastructure for mortgage operations

In a third engagement, Valcon assisted a client suffering from redundant data management processes and suboptimal alignment between data governance administration and technical implementation. These siloed integrations caused severe latency issues and data duplication.

To fix this, Valcon built a self-service catalog interface that enabled Unity Catalog specifically for mortgage use cases. This standardized data exchange solution minimized redundancy and aligned data governance directly with technical execution. The resulting infrastructure consolidation improved resource allocation, lowered consumption costs, and mitigated the risk of regulatory penalties.

Governance as an enabler of strategic advantage

These three projects highlight a broader shift across the Databricks landscape: a growing focus on data governance as organizations scale their data environments and prepare for artificial intelligence.

“In practice, many organizations start with a limited governance foundation: no formal ownership, no defined domains, no established standards, and difficulty enforcing them consistently across the organization. Addressing these gaps alongside the technical implementation is just as important as the implementation itself,” said Emiliya Taranenko, Principal in Data at Valcon.

Additionally, embedding data governance by design into the technical architecture helps organizations embed compliance across the lifecycle and across data domains, lowering the risk of data breaches and regulatory penalties.

For financial institutions, this approach provides a stronger foundation for the future – ensuring that data is resilient, compliant, and ready to support the next generation of AI innovations. Ultimately, effective data governance can turn data from a potential risk into a strategic source of competitive advantage.