Actuarial Table
A statistical chart that shows the probability of certain events occurring based on demographic factors like age, gender, and health status. These tables help insurance companies calculate premiums by predicting how likely someone is to file a claim or, in life insurance, how long they're expected to live.
Example
“The life insurance company's actuarial table showed that a healthy 35-year-old nonsmoking woman has a life expectancy of 82 years, helping determine her monthly premium rates.”
Memory Tip
Think 'Table of Chances' - it's literally a table showing your chances of needing insurance payouts based on who you are.
Why It Matters
Actuarial tables directly determine your insurance costs by placing you into risk categories based on statistical data about people like you. Understanding these tables helps explain why certain demographics pay more for insurance and can help you make informed decisions about coverage timing and amounts.
Common Misconception
Many people believe actuarial tables are discriminatory or unfair, but they're actually based on objective statistical data collected over decades. The tables don't predict what will happen to any individual, but rather show probabilities across large groups of similar people.
In Practice
A mortality table might show that out of 100,000 healthy 40-year-old men, approximately 150 will die within the year. This 0.15% probability helps the insurance company calculate that they need to collect enough premiums to pay death benefits on roughly 150 policies per 100,000 issued. For a $500,000 life insurance policy, the expected payout cost would be $750 per year ($500,000 × 0.0015), though the actual premium would be higher to cover company expenses and profit margins.
Etymology
The term combines 'actuarial' (from Latin 'actuarius' meaning record keeper) with 'table,' referring to the tabular format of statistical data. The first mortality tables were created in the 1690s by Edmund Halley, better known for Halley's Comet.
Common Misspellings
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