Predictive analytics involves building models to predict future results. It’s much more than looking at historical data to understand past results (often called “descriptive analytics” or “business intelligence”). Predicting the future involves separating random events from predictable patterns and requires well-grounded mathematical techniques.
Insurers have come a long way in their use of predictive analytics to deliver better business outcomes. Guidewire has found that insurers typically progress through several phases on their way to becoming efficient.
This white paper introduces a predictive analytics maturity model, discusses the typical issues insurers face in each phase, and recommends best practices for an efficient and agile approach.