What the Client Was Facing
A healthcare insurer had claims data spread across 15 legacy systems with no single source of truth. Actuarial teams spent 3 weeks per month extracting, cleaning and reconciling data. Data errors in pricing models had resulted in significant financial exposure in a previous year.
What ZippyOPS Was Engaged To Do
ZippyOPS was brought in to design and implement a solution addressing the root causes of the client's challenges — delivering measurable outcomes within a fixed engagement timeline. Our team worked embedded with the client's engineers throughout the entire project.
How We Solved It
ZippyOPS built a HIPAA-compliant data lakehouse on Databricks with automated ingestion from all 15 source systems via Airbyte. dbt implemented data quality checks and reconciliation rules, and a data contract framework ensured upstream systems couldn't break downstream models.
Technologies Used
Measurable Outcomes Delivered
Actuarial data preparation time reduced from 3 weeks to 2 days
Data errors in pricing models eliminated through automated quality gates and reconciliation
Single source of truth established across all 15 systems
HIPAA compliance maintained with full data lineage and access audit trail
Want Similar Results for Your Team?
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