Most people are aware that life insurance companies rely on an individual's age, health and lifestyle choices when making a decision whether or not to offer coverage. They evaluate the applicant’s information and classify the applicant based upon their insurance tables. The premium that the applicant pays is directly related to this classification. But how do the insurance companies formulate these tables? How do they arrive at their premium prices? In this article we will attempt to give you a basic understanding of how insurance premiums are calculated.

In insurance, risk refers to the possibility of loss. When a person buys insurance, this risk is transferred form the insured person to the insurer. In order to make a successful business of accepting the transfer of risk, the insurer must determine to some degree how many losses will actually occur. The insurer can’t predict the losses that are expected for any given individual. Using the law of large numbers, however, insurance companies can predict with accuracy how many losses will occur within a group.

The basic principle of the law of large numbers is as follows: the larger the group, the more predictable the future losses in the group will be for a given period of time. The insurance company cannot predict which individual people will die, but with a large enough group being studied, statistics can accurately predict the number of people that will pass away.

An exposure unit is the person or item of property that is insured. In order for the law of large numbers to be effective, a large number of similar, or homogeneous, exposure units must be combined. For life and health insurance purposes, the exposure unit is equivalent to the economic value of the insured person’s life. In other types of insurance it’s the number of homes, cars, or whatever that’s being insured.

The degree of error in predicting losses decreases as the number of individual exposure units increases. In other words, the larger the group, the more closely the predicted losses will approach the actual losses experienced. Insurers only deal with averages; by centering on the average risk, the high and low extremes in loss experience cancel each other out.

Insurance companies employ mathematicians, called actuaries, who study and compile statistical data about exposure units and risks. This data is the basis for the mortality (death) and morbidity (sickness) tables that are used to predict probable future losses due to sickness and death. Of course, these tables take into account many different variables which raise or lower the risk of loss. The insured person is classified, and premiums are set, based upon where his or her profile falls with regard to these tables.

Finally, insurance companies collect premiums to cover expenses, profits, and the cost of predicted losses. These expected losses are based on the past experience of the average risk. The fact that some people live well beyond normal life expectancy (and thus pay premiums for a much longer period of time) is irrelevant, since it can be counted on that others (who have paid very few premiums) will die prematurely. The two extremes cancel each other out, leaving the average risk as the insurance company’s basis for calculating expected losses.