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What Is the Yearly Probability of Living?


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    Highlights

  • The yearly probability of living measures the chance of surviving one more year and is key in life insurance underwriting
  • It is calculated from mortality tables showing death rates by age and other factors
  • Insurers use this data to set premiums, while customers can use it to check for fair pricing
  • Real-world examples highlight variations in life expectancy based on gender, nationality, and health conditions
Table of Contents

What Is the Yearly Probability of Living?

I'm here to explain the yearly probability of living, which is a statistical concept that measures the likelihood that you or a group of people will survive for one more year. You should know it's widely used in the insurance industry to underwrite life insurance contracts. Generally, if you're older, you'll have a lower yearly probability of living, and that means you'll likely face higher insurance premiums.

Key Takeaways

  • The yearly probability of living is a statistical measure of the likelihood of surviving through a given year.
  • It is calculated using data from mortality tables.
  • This measure, and others like it, are an essential part of how insurance companies set their premiums. It is also used by insurance customers to determine whether they are receiving appropriate rates.

Understanding the Yearly Probability of Living

To stay profitable, insurance companies must use all available data to estimate the likelihood that their policyholders will file claims. For life insurance, one of the most important types of data comes from mortality tables, also known as life tables. These resources show the rate of death at each age, expressed in terms of the number of deaths per thousand. By studying these tables, insurers can calculate the yearly probability of living for their policyholders and set premiums accordingly.

In essence, the data in a mortality table is determined by dividing the number of people alive at the end of a given year by the number alive at the beginning of that year. Depending on the table, the data might reflect a broad population, like the entire United States, or a specific subset, such as those aged 70 or older or those with certain pre-existing illnesses.

For insurance purposes, companies select the most relevant data when underwriting their products. So, a life insurance product aimed at senior citizens will use the yearly probability of living for that age group.

I know it can be uncomfortable for many people to think about statistics like the yearly probability of living, as it makes you reflect on your own mortality. This is especially true since, when plotted over time, it declines continuously as you age, eventually reaching 0%. From a financial perspective, however, you can't avoid this data because it's critical for evaluating risk. Insurers use it to calculate claim likelihood and set premiums, and as a policyholder, you should consider it to ensure you're getting a fair price on your life insurance.

Real World Example of the Yearly Probability of Living

Beyond age, other factors considered in calculating these figures include pre-existing health conditions, nationality, gender, ethnicity, and economic status. These are statistically relevant because they correlate with different life-expectancy outcomes.

For instance, women worldwide have a life expectancy roughly 7% higher than men. Globally, women live about 75 years on average, while men live about 70 years. There's also considerable difference between nations. Canadians have an average life expectancy of just under 82 years, whereas Americans live about 79 years on average. In extreme cases, the difference is stark: citizens of Japan have an average of 84 years, but those in the Central African Republic have only 53 years.

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