From Lagging Reports to Lightning Decisions: Analytics Reinvented for Insurance

Client Overview

This insurer manages mountains of policy, claims, and financial data every day. But their legacy analytics setup was slow, expensive, and hard to scale. Analysts were stuck wrangling Excel files. Executives had no visibility until it was too late. They knew the answer wasn’t just new tools—it was a new way of thinking about data. That’s where we came in

Challenges

• Adhering to Traditional Methods: Their on-premise systems and manual ETL tasks created a bottleneck. Each system and software update was a weeks-long endeavor needing IT administrative support.

• Lack of Trust in the Data: Due to inconsistent data formats, lack of governance, and siloed reporting, no one could trust the data. This lack of trust caused indecision concerning many, if not all, major organizational decisions.
  

Solution

• • Current, Organized Data Stack: Using Python frameworks and dbt for orchestrated transformation, we moved everything over to Google BigQuery. We’ve constructed and maintained star schemas, managed jobs through dbt Cloud, and implemented intelligent partitioning to maintain peak performance.
    

  • Functional Self-Service Dashboards: We launched cross-functional and tiered-access dashboards via Looker Studio, serving all organizational levels from underwriting to executives. Alerts and notifications are now obsolete; executives can filter data and make decisions on the spot.
    

Business Impact

• • • Instantaneous Monitoring: Data systems now process data in under 10 minutes, granting executives and directors dynamic snapshots of key performance metrics.
      

    • Better Agility, Lower Expenses: The client was able to reduce overhead and eliminate delays with a scalable cloud infrastructure while shedding legacy bloat and enabling cooperative work across teams driven by shared, trusted data.