
Ultimate Mortality Table
An ultimate mortality table lists the percentage of life insurance purchasers expected to still be alive at each given age, beginning with age 0, which represents 100% of the population, up to age 120. An ultimate mortality table lists the percentage of life insurance purchasers expected to still be alive at each given age, beginning with age 0, which represents 100% of the population, up to age 120. In addition, some might include an aggregate mortality table, featuring death-rate data on the entire study population that has purchased life insurance, without a categorization based on age or time of purchase. Typically, the data is based on a population of life insurance policyholders from either a particular insurance company or group of them, rather than the entire U.S. population. The profitability of insurance products partly hinges on companies accurately analyzing the data behind ultimate mortality tables.

What Is an Ultimate Mortality Table?
An ultimate mortality table lists the percentage of life insurance purchasers expected to still be alive at each given age, beginning with age 0, which represents 100% of the population, up to age 120. Typically, the data is based on a population of life insurance policyholders from either a particular insurance company or group of them, rather than the entire U.S. population.




Understanding an Ultimate Mortality Table
Mortality tables are essentially grids of numbers that show the probability of death for members of a given population within a defined period of time, based on a large number of factored variables.
What mainly separates an ultimate mortality table from other mortality tables is its exclusion of recently underwritten policies. The first few years of life insurance data is usually removed from the analysis to eliminate so-called selection effects. The rationale here is that people who just received life insurance will often have passed a medical exam and, as a result, should be statistically healthier and less likely to be on the brink of death than the rest of the general population.
The year Raymond Pearl introduced the world to mortality tables for the purpose of furthering ecological studies.
The information underlying ultimate mortality tables is called survivorship data and takes into account many risk factors. Along with death and survival rates among age groups and sexes, mortality tables may also list survival and death rates in relation to weight, ethnicity, and region. Some break out statistics for smokers and non-smokers, too.
In addition, some might include an aggregate mortality table, featuring death-rate data on the entire study population that has purchased life insurance, without a categorization based on age or time of purchase. The data in an aggregate table depends on the combined statistics of several, if not many, individual mortality tables.
How an Ultimate Mortality Table Is Used
Insurance companies use data from ultimate mortality tables to price their products and determine whether to offer coverage to an applicant.
Life insurance guarantees a lump sum payment to named beneficiaries when the policyholder dies, so studying the probability that an applicant might pass away during the period he or she seeks coverage for is essential to ensure the profitability of an insurance company.
Important
The profitability of insurance products partly hinges on companies accurately analyzing the data behind ultimate mortality tables.
To a lesser degree, investment-management companies may also consult ultimate mortality tables to help their customers make determinations about their own respective life expectancies and how much money they might need in retirement.
Special Considerations
As is the case for other types of statistical data, the accuracy of ultimate mortality tables depends on the breadth of data in the survey. In other words, an insurance company's ultimate mortality table may not be as precise as one compiled by an organization that's able to compile data sets from multiple insurers.
For instance, the Society of Actuaries (SOA) typically produces an ultimate mortality table each year that is based on a fairly wide data set. It calculates mortalities for both men and women in the U.S., and also includes a blended table with the ultimate mortality of the entire U.S. population.
Related terms:
Accounting
Accounting is the process of recording, summarizing, analyzing, and reporting financial transactions of a business to oversight agencies, regulators, and the IRS. read more
Actuarial Assumption
An actuarial assumption is an estimate of an uncertain variable input into a financial model for the purposes of calculating premiums or benefits. read more
Aggregate Mortality Table
Aggregate Mortality Table is data on the death rate of everyone who has purchased life insurance, without categorization based on age or time of purchase. read more
Beneficiary
A beneficiary is any person who gains an advantage or profits from something typically left to them by another individual. read more
Insurance
Insurance is a contract (policy) in which an insurer indemnifies another against losses from specific contingencies and/or perils. read more
Investment Management
Investment management refers to the handling of financial assets and other investments by professionals for clients, usually by devising strategies and executing trades within a portfolio. read more
Life Insurance Guide to Policies and Companies
Life insurance is a contract in which an insurer, in exchange for a premium, guarantees payment to an insured’s beneficiaries when the insured dies. read more
Mortality Table
A mortality table shows the rate of deaths occurring in a defined population during a selected time interval or survival from birth to any given age. read more
Profit
Profit is a financial benefit that is realized when the amount of revenue gained from a business activity exceeds the expenses, costs, and taxes needed to sustain the activity. Any profit that is gained goes to the business's owners. read more
Retirement
Retirement refers to the time of life when one chooses to permanently leave the workforce behind. read more