For this study, we provided Munich Re with a deidentified dataset of over 40 million lives drawn from U.S. insurance applicants between 2005 and 2020. The reinsurer found that:
- Adding Medical Data to the standard Risk Score 3.0 model (with scores based on Prescription Data) results in a significantly improved hit rate and improved risk stratification
- Scores with a Medical Data hit are notably more effective at identifying both the lowest and highest mortality risks versus scores with a Prescription Data hit only
- The addition of Medical Data makes Risk Score particularly effective at segmenting mortality in the demographic sweet spot for life insurance carriers—applicants aged 30 to 59
Munich Re also noted that the addition of Medical Data to Risk Score 3.0 greatly improves the model’s effectiveness as an accelerated underwriting tool. Holding mortality constant, straight-through processing rates increased from 56% (Prescription Data only) to 71% (Prescription Data and Medical Data). Read the study.
Prefer watching to reading? You can view Munich Re’s video overview of the study, presented by Cherry Wang, FSA, MAAA.