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What Is an Ultimate Mortality Table?


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    Highlights

  • Ultimate mortality tables show survival rates for life insurance policyholders, excluding data from recently underwritten policies to avoid bias from healthier individuals
  • These tables are based on policyholder data from specific companies, not the entire population, and help insurers price products and decide on coverage
  • They incorporate various risk factors like age, sex, weight, ethnicity, region, and smoking status for detailed survivorship analysis
  • Insurance profitability relies on accurate analysis of these tables, and broader data sets from organizations like the Society of Actuaries provide more precise mortality statistics
Table of Contents

What Is an Ultimate Mortality Table?

Let me explain what an ultimate mortality table is. It's a table that provides the percentage of life insurance policyholders expected to reach each age listed. You see, it starts at age 0 with 100% of the population and goes up to age 120. The data usually comes from policyholders of a specific insurance company or a group of them, not the whole country's population.

Key Takeaways

  • An ultimate mortality table shows the expected survival rates of life insurance policyholders.
  • Typically, the data is based on policyholders from a particular insurance company or group of them, rather than the entire U.S. population.
  • Ultimate mortality tables exclude data from recently underwritten policies because their owners were probably required to pass a medical exam.
  • Insurance companies consult ultimate mortality tables to price their products and determine whether to offer coverage to an applicant.

Understanding Ultimate Mortality Tables

Mortality tables are grids of numbers showing the probability of death for a population over a defined period, based on many variables. What sets an ultimate mortality table apart is that it excludes recently underwritten policies. We remove the first few years of data to eliminate selection effects. The reason is straightforward: people who just got life insurance often passed a medical exam, making them healthier and less likely to die soon compared to the general population.

Back in 1921, Raymond Pearl introduced mortality tables for ecological studies. The data in these tables, called survivorship data, accounts for risk factors. It includes death and survival rates by age, sex, weight, ethnicity, region, and even separates smokers from non-smokers.

Some tables include an aggregate mortality table, which has death-rate data for the entire study population of life insurance buyers, without breaking it down by age or purchase time. This aggregate data comes from combining several individual mortality tables.

How an Ultimate Mortality Table Is Used

Insurance companies use these tables to price products and decide if they'll offer coverage to an applicant. Life insurance pays a lump sum to beneficiaries when the policyholder dies, so calculating the probability of death during the coverage period is key to the company's profitability.

The profitability of insurance products depends on accurately analyzing the data in these tables. To a lesser extent, investment-management companies use them to help clients estimate life expectancies and figure out retirement savings needs.

Special Considerations

The accuracy of ultimate mortality tables relies on the breadth of the data. A single company's table might not be as precise as one from an organization compiling data from multiple insurers. For example, the Society of Actuaries produces an annual ultimate mortality table based on a wide data set. It calculates mortalities for men and women in the U.S., and includes a blended table for the entire population.

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