About
This project involved building a custom data analysis tool for a U.S. insurance provider struggling with large-scale data analysis. The solution enables real-time data processing, interactive dashboards with flexible filtering, and profitability analysis by industry vertical. We also developed a predictive model to identify profitable insurance cases and a reporting system highlighting key drivers of loss and profit across metrics.
Challenge, approach, and impact
Insurance Profitability Analysis at Scale
The client struggled to analyze a large volume of tabular insurance data to understand profitability across individual cases and industry segments. Existing data could not support real-time analysis, flexible filtering, or profitability forecasting. The client needed a custom solution capable of processing large datasets, visualizing profit and loss drivers, and identifying patterns that indicate profitable insurance cases.
How we built
Testimonials
Sean B.
Insurance provider
“Great work! The team provided an excellent solution for consolidating our data from multiple sources and creating valuable insights for our business.“
Team structure
Client team
Sean B
CEO
Project stakeholder
The client stakeholders were working closely with the team at Dataforest
Agency team
5 x Data Engineer
Production
2 x Product Manager
Production
1 x Business Analytics
Production
