- Operational Versus Traditional Analytics
- Key Insurance Analytics
- Challenges
- Insurance Analytics Evolution
- Summary
- Key Terms
- Additional Resources/Reading
Insurance Analytics Evolution
Insurers increase their analytic maturity as they improve their data management and metric sophistication. As they increase data granularity and data quality and integrate it across more than one functional area or business domain, they enable more sophisticated analytics. Similarly, as they measure not only historical key performance indicators but also the leading indicators (or driving analytics), they also enable more predictive analytics within and across functional areas.
Figure 1-4 reviews the maturity evolution for a subset of insurance processes: marketing, product development, pricing, underwriting, and claims. The overall industry analytic maturity is indicated with the dots. A useful exercise is for individual organizations to assess their maturity, compare it to where they aspire to be, and to identity the hurdles that keep them from reaching their desired state. Following this self-assessment, they can define plans to address areas of needed improvement to reach their next level of maturity and use analytics for strategic competitive advantage.
Figure 1-4 Insurance Analytics Evolution