Case Study: Leading Global Insurance Company achieves 1.5% reduction in cancellation rates with Angoss KnowledgeSTUDIO

How a Global Insurance Brand Decreased their Cancellation Rates by 1.5%

A leading global insurance company—founded in the 18th century, with about 160,000 employees and over 100 million customers—was experiencing higher-than-normal mid-term cancellations of home insurance policies. The insurer needed a predictive model to identify policies at risk of cancellation (looking 14 days after inception and 28 days before renewal) on segmented datasets to reduce customer churn and lower risk.

Using Angoss KnowledgeSTUDIO the company built and tested a predictive model that incorporated nationwide policy data (premiums, product types, payment methods, policy age and holder demographics), targeted the top 2.5% most likely to churn, and scored results over a three-month test. A controlled marketing trial showed an 11% improvement versus non-controlled data and a 1.5% reduction in cancellations (about 35 policies saved at an average premium of £237); the model is now used monthly to boost retention and loyalty.