Credit data is a valuable source of information for life insurers, as it can reveal insights into the financial behavior and stability of applicants. But how does credit data interact with other types of data, such as prescription drug and medical billing data, to predict mortality risk?
In a new white paper, RGA experts Mark Ma, Guizhou Hu, and Taylor Pickett present the results of their actuarial validation of Milliman Irix® – Risk Score 3.0 with Credit, a commercial risk-scoring product that combines prescription drug, medical billing, and credit data to generate four different scores for mortality risk segmentation.
The study compared the performance of the four models and scores, namely Rx3.0, RxDx3.0, RxCr3.0, and RxDxCr3.0, and found that:
- All four products are effective in segmenting mortality, but the most powerful one is RxDxCr3.0.
- Adding credit data to Rx and RxDx scores can improve the risk segmentation, both at the low-risk and high-risk ends of the spectrum.
- Credit and medical-based scores rank mortality risks differently, meaning that they capture different aspects of risk and can complement each other.
- The value of the scores varies by population characteristics and durations and depends on the objectives and use cases of the underwriting program.
Read the white paper for a comprehensive analysis of the Milliman Irix - Risk Score 3.0 with Credit, and to find out how credit data can enhance mortality risk prediction.
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