Final answer:
To determine premium rates for a Whole Life policy, an insurance company focuses on risk classification. In a hypothetical scenario, different premiums would be calculated for two groups of men with different risks of dying in the next year, based on family history of cancer. Combining them into a single group without differentiation could lead to underpricing for the higher risk individuals.
Step-by-step explanation:
When an insurance company determines the premium rates for a Whole Life policy, the key factor they consider is the applicant's risk classification. This entails evaluating the potential policyholder's likelihood of filing a claim, which is influenced by their health status, lifestyle, occupation, and family medical history, among other things.
In the provided scenario, 20% of a group of 1,000 50-year-old men has a family history of cancer and thus a higher risk (1 in 50 chance) of dying in the next year. The other 80% without such a family history have a lower risk (1 in 200 chance) of dying in the next year. If the insurer were selling life insurance separately to each group, they would calculate the actuarially fair premium accordingly.
To calculate the actuarial premium for each group:
- Group with family history of cancer: (20% of 1,000 men) * (1/50 chance of dying) * $100,000 = $40,000 total expected payout, which means each person in this group would have an actuarially fair premium of $2,000.
- Group without family history of cancer: (80% of 1,000 men) * (1/200 chance of dying) * $100,000 = $40,000 total expected payout, which means each person in this group would have an actuarially fair premium of $500.
If the insurance company were offering life insurance to the entire group without knowing family cancer histories, the actuarially fair premium would be:
- Total expected payout: ($40,000 from first group) + ($40,000 from second group) = $80,000
- Total premium for the group as a whole: $80,000 / 1,000 men = $80 per person
Applying the actuarially fair premium to the entire group, without differentiating the risk, could lead to adverse selection where higher-risk individuals would be more likely to buy the insurance, knowing their own risk factors. This could cause the insurance company to have a deficit if the number of claims exceeds the expected amount based on the undifferentiated rate.