Insurance And the Law of Large Numbers

The law of large numbers: Probability and statistics state that as a sample size grows the mean number gets closer to the average number of the entire population studied. The more similar the life or health insurance cases that are studied, the closer an insurance company can get to a predictable probability.

Cases that typically do not conform to the law of large numbers are impaired risk cases. An example of an impaired risk may be someone that has had multiple heart attacks, or someone that participates in a risky hobby such as sky-diving. Impaired risk cases simply have too many variables involved to conform to the law of large numbers. Think about all the different diseases and the complications of having multiple health issues. Think of all the interactions between these different medical conditions and how different combinations of diseases lead to different outcomes.

For a life insurance company, properly pricing an impaired risk case is more important today than ever before. The unexpected can, and has, happened such as COVID-19. Life expectancy has declined in the last few years, and income for the insurer from investments has declined as well. This has resulted in a one-two punch for life insurance companies. Adding to their troubles when it comes to underwriting impaired risks, physicians that the insurance companies have relied on for years that specialize in substandard cases are retiring. Their replacements are often much less experienced in genetics and informatics.

Impaired risk life insurance cases today will require even more detail than before. Obtaining Attending Physician Statements (APS’s) and supporting information is a must. These cases will also require a trusted broker that has a good existing relationship with underwriters.