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How Life Insurance A Company sells a Term Insurance Policy to a 21-Year-Old Male That Matches the Life Expectancy Let's say you want to randomly choose a male from a pool of males who have been invited to a birthday party. That guy is then asked to take a questionnaire that asks him about his sex and age. If he is over twenty-five years old and not married, then he is put into a mortality table. Once in a mortality table, if he dies during the next five years, then the insurance company pays you money even if he is not in the mortality table. So what kind of situations can result in a young male being added to a mortality table? The most common ones would include a divorce or the death of a parent. insureinfoq.com who are constantly living with their mothers as part of a family unit tend to be at a higher risk of death. In addition, young men who are under 25 years old without a dependent partner tend to be at a higher risk because they have not established a health history yet. A healthy male who is insuring one individual person through a joint account is at a much lower risk. So what does the insurance company to collect a premium of if the insured dies within the next five years? The answer depends on how the mortality tables were generated. Suppose the age is twenty-five years and the male has a low expectancy index. He is then assigned a mortality table based on his age, gender, and current health status. If he were to die suddenly today out of those designated ages, what would be the amount the insurance company would charge? This example is admittedly simplistic, but it illustrates the point. If the expected life span of the insured is short by five years, then the expected life span of the beneficiary is very short as well. If the expected life span is very long, the beneficiary may be long-lived. If the life expectancy is very short, the beneficiary may be very young. In both cases, the life insurance company earns nothing on the policy. Now suppose the same hypothetical situation but this time assume the insured dies five years later. The life expectancy of the insured has increased to seventy years old. If the expected life span has gone up by five years, the standard deviation of the random variables is greater. Therefore, the insurance company must charge a higher premium. It's possible to solve for the normal distribution and the log-normal distribution. By plugging in the data for the age and water temperature, we get a distribution called the chi-square (sometimes referred to as the Starnes-Gould chi-square distribution). With the help of this chi-square distribution, we can solve for the standard deviation and we find that it is significantly greater than one. So, it turns out that Mr. Starnes and Mr. Michaels have discovered something interesting. Now suppose the company collects a regular premium and assumes that the person they are charging a low premium to will live for the expected lifetime. They could use any number of different mortality tables to calculate the risk premium. However, using a single mortality table to calculate the risk premium would be much more efficient. If they use a normal, logistic distribution with one variable set at one percent and five random variables, they find that the average lifetime lifespan of the person they are charging a normal premium to is about eighty years old, which is much more realistic.
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