
Yearly Probability of Living
The yearly probability of living is a statistical concept that measures the likelihood that a given person, or group of people, will survive for one more year. Whereas insurers use this data to calculate the likelihood of insurance claims and set their premiums accordingly, policyholders must also consider them in order to determine whether they are receiving a fair price on their life insurance. Whereas citizens of Japan have an average life expectancy of 84 years, the citizens of the Central African Republic have an average life expectancy of only 53 years. For life insurance policies, one of the most important types of data consists of mortality tables, also known as life tables. A life insurance product marketed to senior citizens, therefore, will be underwritten using the yearly probability of living for that age cohort.

What Is the Yearly Probability of Living?
The yearly probability of living is a statistical concept that measures the likelihood that a given person, or group of people, will survive for one more year. It is widely used in the insurance industry to underwrite life insurance contracts. Generally speaking, older individuals will have a lower yearly probability of living and will therefore likely be charged higher insurance premiums.



Understanding the Yearly Probability of Living
In order to be profitable, insurance companies must use all available data to estimate the likelihood that their policyholders will file insurance claims. For life insurance policies, one of the most important types of data consists of mortality tables, also known as life tables. These important 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 corresponding to their policyholders, setting their insurance premiums accordingly.
In essence, the data shown in a mortality table is determined by dividing the number of people alive at the end of a given year by the number of people alive at the beginning of that same year. Depending on the mortality table in question, the data may reflect a broad population, such as for the United States as a whole, or it might reflect a specific subset of that population, such as those aged 70 or older or those possessing certain pre-existing illnesses. For insurance purposes, companies will select the most relevant data possible when underwriting their insurance products. A life insurance product marketed to senior citizens, therefore, will be underwritten using the yearly probability of living for that age cohort.
For many people, it can be uncomfortable to consider statistics such as the yearly probability of living, because it forces us to reflect on our own mortality. This is especially true considering that, when plotted over time, the yearly probability of living declines continuously as we age, eventually reaching 0%. From a financial perspective, however, this type of data is impossible to avoid because it is critical in evaluating risk. Whereas insurers use this data to calculate the likelihood of insurance claims and set their premiums accordingly, policyholders must also consider them in order to determine whether they are receiving a fair price on their life insurance.
Real World Example of the Yearly Probability of Living
In addition to age, other factors that are often considered when calculating these figures include the population’s pre-existing health conditions, nationality, gender, ethnicity, and economic status. These factors are considered statistically relevant because they have been shown to correlate with different life-expectancy outcomes.
For instance, women worldwide have been shown to have a life expectancy roughly 7% higher than men. Globally, women live for roughly 75 years on average, whereas men live for about 70 years. There is also considerable difference between nations. For example, Canadians have an average life expectancy of just under 82 years, whereas Americans live for approximately 79 years on average. In some cases, the difference between countries’ yearly probability of living can be very extreme. Whereas citizens of Japan have an average life expectancy of 84 years, the citizens of the Central African Republic have an average life expectancy of only 53 years.
Related terms:
Actuarial Age
Actuarial Age is an individual's life expectancy based on calculations and statistical modeling. 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
Insurance Premium
An insurance premium is the amount of money an individual or business pays for an insurance policy. read more
Life Expectancy
Life expectancy is defined as the age to which a person is expected to live, or the remaining number of years a person is expected to live. 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
Preexisting Condition
A preexisting condition is an illness or health condition that existed prior to applying for health or life insurance. read more
Risk Management in Finance
In the financial world, risk management is the process of identification, analysis, and acceptance or mitigation of uncertainty in investment decisions. read more
Ultimate Mortality Table
An ultimate mortality table lists the percentage of life insurance policyholders, bar recent additions, expected to still be alive at each given age. read more