What Is the Mortality Table Definition and How Is It Used?

A mortality table is a fundamental tool in finance and insurance, estimating life expectancies and death probabilities at various ages. Built using historical data and statistical models, these tables guide decisions on financial products tied to longevity. Accurate life expectancy predictions are essential for managing risk in pension planning, insurance pricing, and annuity structuring.

Core Data Points in a Mortality Table

A mortality table quantifies survival and death probabilities by age. The qx value represents the probability that a person of a given age will die before their next birthday, based on demographic studies updated periodically to reflect medical advancements and lifestyle changes.

The lx value indicates the number of individuals, out of an initial population (often 100,000), expected to be alive at a specific age. This helps insurers and pension funds project how many policyholders or beneficiaries will continue receiving benefits. The dx value refines longevity projections by showing the number of people expected to die within a given age interval.

The ex value, or life expectancy at a given age, adjusts for the fact that an individual has already survived to a certain point. For example, while the average U.S. life expectancy at birth might be 77 years, a 65-year-old may have an additional 18 years of expected life due to having already surpassed earlier mortality risks.

Types of Mortality Tables

Mortality tables vary based on their purpose, accounting for gender, health status, and industry-specific risks. The choice of table significantly impacts financial projections.

Static vs. Generational Mortality Tables

A static mortality table provides a snapshot of mortality rates at a given time, assuming they remain unchanged. It is useful for short-term calculations like immediate insurance premiums or pension liabilities but does not account for improvements in life expectancy, which can lead to underestimating longevity risk.

A generational mortality table incorporates projected improvements in mortality rates, adjusting life expectancy estimates based on expected advancements in healthcare and demographic trends. This makes it more suitable for long-term financial planning, such as pension funding and annuity pricing. For example, the Society of Actuaries’ MP-2021 improvement scale is commonly used in the U.S. to update generational mortality tables.

Period vs. Cohort Mortality Tables

A period mortality table reflects mortality rates for a specific calendar year, applying the same rates to all individuals regardless of birth year. It is useful for analyzing historical mortality trends but does not account for future changes.

A cohort mortality table tracks a specific group of individuals born in the same year and adjusts mortality rates based on observed and projected trends for that cohort. This approach is particularly useful for pension and insurance calculations, as it provides a more realistic estimate of future longevity. For instance, if medical advancements significantly reduce mortality rates for individuals born after 1980, a cohort table would reflect this improvement, whereas a period table would not.

Ultimate vs. Select Mortality Tables

An ultimate mortality table applies to individuals who have been insured for several years, excluding the effects of underwriting selection. It is commonly used for long-term financial planning, such as evaluating pension fund sustainability or pricing long-duration insurance policies.

A select mortality table accounts for underwriting selection, differentiating mortality rates based on how recently an individual was underwritten. Newly insured individuals typically have lower mortality rates due to medical screening. Over time, their mortality rates converge with those in an ultimate table. This distinction is particularly relevant in life insurance pricing, where insurers use select tables for new policyholders and ultimate tables for long-term risk assessment.

Applications in Pension Funding Calculations

Mortality tables help pension funds estimate future obligations by projecting the number of participants expected to draw benefits each year. This is especially important for defined benefit (DB) plans, where employers commit to lifetime payments for retirees. Underestimating longevity can lead to funding shortfalls, while overestimating it may reduce capital available for other business needs.

The Actuarial Standards of Practice (ASOP), particularly ASOP No. 35, guides actuaries in selecting appropriate mortality assumptions for pension valuations. Many U.S. plans use mortality tables published by the Society of Actuaries (SOA) and Internal Revenue Service (IRS), such as the Pri-2012 table, based on private-sector pension data. The IRS updates its mortality assumptions annually for minimum funding requirements under the Employee Retirement Income Security Act (ERISA). These assumptions impact the present value of liabilities, influencing employer contributions needed to maintain plan solvency.

Mortality assumptions also affect lump-sum distributions. When retirees opt for a one-time payout instead of lifetime payments, the plan must convert future expected benefits into a present-value amount. The IRS prescribes mortality tables for this calculation, along with a mandated discount rate under Internal Revenue Code (IRC) Section 417(e)(3). Lower assumed mortality rates increase lump-sum payouts, as retirees are expected to live longer, raising the plan’s financial burden.

Utilization in Insurance Premium Determinations

Pricing life insurance policies requires a precise assessment of risk. Mortality tables provide insurers with statistical foundations to estimate the likelihood of policyholder death, directly influencing premium structures.

Beyond setting base rates, insurers segment applicants into risk classes based on mortality expectations. Factors such as smoking status, medical history, and occupation influence classifications. A preferred risk policyholder with no major health issues may be assigned a lower mortality probability than the standard population, resulting in reduced premiums. Conversely, applicants with elevated health risks—such as diabetes or a history of heart disease—may see their rates adjusted upward.

For term life insurance, mortality projections determine the probability that a policyholder will pass away within the policy’s fixed duration. If a 40-year-old male non-smoker has a 0.2% annual mortality rate from actuarial tables, insurers can calculate expected payouts and set premiums accordingly. For permanent life insurance, longer time horizons require additional considerations, such as interest rate assumptions and lapse rates, which affect long-term reserve requirements.

Role in Annuity Evaluations

Mortality tables are fundamental in structuring annuities, which provide periodic payments for as long as an individual lives. Since annuity providers bear the risk of longevity, accurate life expectancy estimates ensure financial sustainability. Longer life expectancies result in lower periodic payments to balance the insurer’s risk.

In immediate annuities, where a lump sum is exchanged for lifelong disbursements, mortality projections determine the payout amount. If a 70-year-old male is expected to live another 15 years based on actuarial data, the insurer spreads the lump sum over that period while factoring in investment returns. Deferred annuities, which accumulate funds before payouts begin, rely on mortality tables to estimate the likelihood of policyholders reaching the payout phase. Insurers also adjust for adverse selection, as annuity buyers tend to be healthier than the general population, leading to longer-than-average life expectancies.

Incorporation in Life Settlement Assessments

Life settlements involve selling an existing life insurance policy to a third party for a lump sum, typically at a value higher than the policy’s cash surrender amount but lower than its death benefit. Mortality tables are integral to pricing these transactions, as investors seek to estimate the time horizon for receiving the policy’s payout. A shorter projected lifespan increases the policy’s market value, as the buyer will collect the death benefit sooner.

To refine these estimates, life settlement providers use underwriting-based mortality tables, incorporating medical records, prescription histories, and lifestyle factors. Unlike standard population tables, these models adjust for individual health conditions, providing a more tailored life expectancy projection. Regulatory requirements, such as those set by the National Association of Insurance Commissioners (NAIC), mandate transparency in mortality assumptions to protect policyholders from undervaluation.