Data Analytics
Consultants: Jessica Hudzik, Teri Ferris, Kiran Lokhande
A multibillion-dollar specialty insurance provider was rapidly expanding through mergers and acquisitions, bringing together the data from brokers, third-party administrators (TPAs), and legacy systems at an unprecedented pace. While this growth strategy fueled revenue, it also introduced significant data complexity across premium and loss data sources. The organization partnered with Green Leaf to design a scalable, future-ready data foundation that could keep pace with acquisition growth while improving financial reporting accuracy and timeliness.
Rapid M&A growth left the organization managing premium and loss data across dozens of disconnected systems, formats, and spreadsheets, making financial reporting slow, manual, and error-prone.
Green Leaf designed and implemented a flexible Azure-based data lake and Data Vault architecture that standardized disparate data sources and dramatically simplified onboarding of new acquisitions.
As the organization acquired new brokers and TPAs, each came with its own way of storing and reporting data. Premium and policy data lived across a mix of legacy OLTP systems, newer web-based platforms, and countless Excel files—each with different formats, structures, and business logic. Claims and loss data from TPAs presented similar challenges, with overlapping data points stored inconsistently across providers.
Because this data had to be manually transformed to fit legacy financial processes, the client struggled to meet reporting SLAs and lacked confidence in the completeness and quality of its data. While premium data was partially usable, loss and claims data from TPAs was largely underutilized, limiting the organization’s ability to see a true end-to-end view of its business.
The core challenge was clear: the client needed a scalable, flexible data solution that could rapidly onboard new acquisitions, support existing financial processes, and serve as a foundation for future analytics and reporting.
Green Leaf partnered closely with the business and technical stakeholders to design a modern data architecture built on Microsoft Azure, using Azure Data Lake Storage and Azure Synapse. A Data Vault modeling approach was selected to provide the agility and scalability required for ongoing M&A activity.
The engagement began with a proof of concept demonstrating that diverse flat file formats—regardless of layout, tabs, or structure—could be ingested into a common staging layer using PySpark and Spark SQL. Metadata-driven mapping tables allowed new flat file sources to be onboarded simply by updating configuration, rather than rewriting code.
Next, Green Leaf implemented a Data Vault model consisting of hub, satellite, and link tables. This enabled the team to standardize core business entities—such as policy transactions and premium amounts—while preserving source-specific attributes and maintaining full historical tracking.
As the project progressed, Green Leaf expanded the solution to include data from multiple OLTP systems. Working with business subject matter experts and leveraging extensive data profiling, the team aligned OLTP data to the same Data Vault entities used for flat files. This approach allowed new attributes and entities to be added seamlessly without redesigning the data model.
Finally, business rules were applied to conform and aggregate data for specific financial and analytic use cases, ensuring that premium and loss data from all sources could be interpreted consistently and accurately.
The new data platform dramatically reduced the time required to onboard new premium and loss data sources, enabling the organization to keep pace with continued M&A activity while meeting financial and reporting SLAs.
By consolidating premium and loss data into a single, governed environment, the client gained visibility into claims and loss data that had previously gone largely unused. This transparency surfaced data quality issues across both internal systems and third-party providers, allowing the organization to address discrepancies and improve overall data integrity.
With a unified view of premium and loss activity, the client transformed its claims and financial workflows, gaining a clearer, end-to-end understanding of business performance. The solution not only supported current operations, it also established a scalable foundation that can be reused to solve similar data challenges across the specialty insurance industry.
Discover how Green Leaf Consulting Group’s strategic IT solutions can bring you growth through technology. Contact Neil McCole at neilm@greenleafgrp.com or (484) 535-4405.