Ultimate Mortality Table: What It Is, How It Works

An ultimate mortality table shows the percentage of life insurance purchasers who are predicted to be alive at each age, starting at age 0, which represents 100% of the population, and ending at age 120. Rather than the total US population, the data is usually based on a population of life insurance policyholders from a certain insurance company or group of firms.

Understanding an Ultimate Mortality Table

Mortality tables are essentially grids of numbers that depict the likelihood of death for individuals of a certain group over a set period of time, based on a large number of factored variables.

What distinguishes an ultimate mortality table from other mortality tables is the absence of freshly endorsed policies. The first few years of life insurance data are typically excluded from the analysis to eliminate so-called selection effects. The reasoning for this is that persons who have just got life insurance will have likely passed a medical exam, making them statistically healthier and less likely to be on the verge of death than the general population.

The information used to generate ultimate mortality statistics is known as survivorship data, and it takes into consideration a variety of risk variables. Mortality tables may include survival and death rates by weight, ethnicity, and geography, in addition to death and survival rates by age group and gender. There is also some separate data for smokers and nonsmokers.

In addition, some may offer an aggregate mortality table, which displays death-rate data for the whole study population who has acquired life insurance, without regard for age or time of purchase. The data in an aggregate table is based on the pooled statistics of multiple, if not many, separate mortality tables.

How an Ultimate Mortality Table Is Used

Insurance firms utilize data from ultimate mortality tables to price their products and decide whether to insure an applicant.

Life insurance guarantees a lump sum payment to named beneficiaries when the policyholder dies, therefore determining the likelihood that an applicant will die within the time for which coverage is sought is critical to an insurance company's profitability.

To a lesser extent, investment management firms may reference ultimate mortality statistics to assist their clients in determining their own life expectancies and the amount of money they would require in retirement.

Special Considerations

The accuracy of final mortality tables, like that of other sorts of statistical data, is determined by the survey's breadth of data. In other words, an insurance company's ultimate mortality table may be less precise than one created by an entity that can combine data sets from various insurers.

For example, the Society of Actuaries (SOA) normally publishes an ultimate mortality table each year based on a pretty large dataset. It estimates mortality rates for both men and women in the United States, as well as a blended table that shows the eventual mortality rate for the total population.