In today’s rapidly evolving financial landscape, data isn’t just a resource — it’s a competitive advantage. Whether it’s underwriting loans, refining investment strategies, or tailoring personalized experiences for clients, financial institutions depend on accurate, accessible data to stay ahead of risk, seize new opportunities, and meet growing customer expectations.

Fivetran delivers automated, secure data integration that, when paired with the scalable, governed Databricks Lakehouse platform, enables financial organizations to centralize, analyze, and activate their data for advanced analytics and AI/ML. Additionally, with optional reverse ETL tools like Census, now a Fivetran company, teams can close the loop by syncing insights directly back into operational systems where decisions are made.

What role does data play in financial services?

Financial institutions are navigating growing pressure to do more with their data — and to do it faster. From high-stakes risk modeling to real-time fraud detection, the need for modern infrastructure is clear. But legacy data architectures often fall short, limiting how quickly data can be accessed, shared, or trusted across the organization.

Fivetran and Databricks provide a modern stack that allows financial services teams to:

• Unify structured and unstructured data across ERPs, EHRs, third-party sources, trading platforms, CRM systems, and more.
• Enable real-time and predictive analytics for sharper forecasting and deeper customer insights.
• Meet compliance requirements
• Accelerate AI and ML adoption with analytics-ready pipelines and scalable compute.

Common data challenges in the industry

Even as the industry accelerates its digital transformation, the gap between what’s possible and what’s practical continues to widen — exposing inefficiencies, inflating costs, and increasing compliance risk. Teams are being asked to deliver more actionable insights, faster — but are often held back by brittle systems, fragmented tooling, and an overreliance on manual work.

Despite the promise of data, many firms still face legacy roadblocks:

• Manual ETL and rising operational costs: Engineering teams are burdened with building and maintaining fragile pipelines, diverting resources from strategic work.
• Data silos and slow decision-making: Teams work in disconnected systems, delaying time-to-insight and increasing duplication across the business.
• Security and regulatory pressure: Sensitive data must be encrypted, masked, and traceable — requiring robust governance without stifling access.
• Retention and experience gaps: Without a complete view of customers, teams struggle to deliver timely, personalized experiences that foster loyalty.

Fivetran and Databricks are built for the future of financial services

Fivetran and Databricks combine to combat the common challenges organizations face when it comes to financial services data — offering a powerful foundation for financial institutions looking to modernize and scale their data infrastructure. 

Fivetran simplifies the process of building and maintaining pipelines by automating data movement from hundreds of sources into any cloud or hybrid environment — with no manual upkeep required. Its low-code approach empowers more teams to explore and operationalize data without relying solely on engineering, accelerating time to insight across the organization. Fivetran also delivers enterprise-grade security and compliance with features like encryption in transit and at rest, column masking, advanced role-based access controls, HIPAA BAA support, and column-level lineage — ensuring traceability, audit readiness, and data governance at scale. Plus, with Fivetran’s acquisition of Census, organizations can now sync trusted models back into tools like Salesforce, HubSpot, and Marketo to power personalized, data-driven operations — freeing up engineering time and getting data back into the hands of the users who will need it.

Paired with Databricks, this joint solution gives financial services teams unmatched flexibility for analytics, machine learning, and AI workloads. Databricks Lakehouse architecture unifies governance (via Unity Catalog), scalable storage, and elastic compute, enabling analytics teams to process structured, semi-structured, and unstructured data on a single, secure platform. Organizations can support both real-time and batch use cases, and rapidly build, deploy, and iterate on AI and ML models — unlocking new insights and driving innovation in areas like investment analytics, underwriting, and customer personalization.

Real-world impact: How NAB meets critical use cases with Fivetran and Databricks

While many financial services institutions continue to grapple with complex data challenges, those leveraging Fivetran and Databricks are overcoming legacy limitations and unlocking new value across critical areas. Take National Australia Bank (NAB), one of the world’s largest financial institutions, for example. 

NAB is modernizing its data infrastructure with Fivetran and Databricks to unlock new capabilities across personalization, analytics, and underwriting — all while improving operational efficiency and reducing costs:

• Hyper-personalization: NAB is using genAI to personalize customer communications and improve engagement through smarter, faster responses. With Fivetran centralizing over 200 siloed data sources in near real time, the bank can power genAI tools like chat assistants that scan internal knowledge bases to support banker responses — leading to faster service and stronger customer retention. These initiatives also support refined, AI-led marketing campaigns tailored to each customer’s personality and behavior.
• Investment analytics: With reliable, unified access to investment data through Fivetran’s change data capture (CDC), NAB has improved the accuracy and performance of machine learning models by 30%. The move from brittle batch pipelines to automated, real-time replication into a Databricks lakehouse has accelerated reporting cycles and enabled deeper portfolio and risk insights — helping teams act on opportunities faster while reducing storage and processing costs by 50%.
• Underwriting: Fivetran’s automated pipelines also power NAB’s AI-led document review workflows. As a result, processing time for trust deed reviews has dropped from 45 minutes to just 5, saving the bank an estimated 10,000 hours annually. With sensitive data flowing through a secure architecture — including Hybrid Deployment to keep processing inside NAB’s environment — the bank meets tight SLAs without sacrificing auditability or compliance.

“Removing complex legacy technology from our ecosystem and replacing it with Fivetran and Databricks to unify our data has been the springboard to enable all of the exciting generative AI use cases we are pursuing.”
— Joanna Gurry, Executive of Data Platforms, NAB

NAB is proving how a modular data stack built on Fivetran and Databricks can drive transformation across the entire financial services enterprise.

Ready to modernize your financial data stack?

Together, Fivetran and Databricks enable financial services institutions to move faster, act smarter, and scale securely. Whether you’re just getting started or optimizing existing workflows, our combined solution gives your teams the foundation they need to drive real results. Explore our Fivetran for Financial Services page for more details.

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