Case Study: a leading healthcare insurance company identifies high-risk customer segments with Quantzig's insurance analytics

Customer Lifetime Value Analysis Helps a Leading Healthcare Insurance Company to Identify High-Risk Customer Segments

Quantzig worked with a leading healthcare insurance company that was struggling with fragmented data across departments, limited customer insights, manual fraud detection, and inefficient underwriting models. These issues created operational silos, slowed claims handling, and made it harder to personalize engagement and manage risk in a highly competitive market.

Quantzig implemented an analytics solution that integrated structured and unstructured data sources, applied machine learning for fraud detection, and built customer lifetime value models to improve segmentation and engagement. The results included a fraud detection rate increase from 65% to 90%, claims processing time reduced from 7 days to 3 days, and customer retention improved from 70% to 85%, demonstrating the impact of Quantzig’s data-driven insurance analytics approach.