Actuarial Assumption

What Is an Actuarial Assumption?

An actuarial assumption is an estimate of an uncertain variable input into a financial model, normally for the purposes of calculating premiums or benefits. Actuarial assumptions involve mathematical and statistical models designed to evaluate risk and probabilities for a particular event. Actuarial assumptions have broad applications, including in the finance industry, economics, computer programming, and in the insurance industry.

An actuarial assumption might include predicting a person's lifespan given their age, gender, and health conditions. Actuaries use large tables of statistical data that correlate the uncertain variable to a variety of key predictive variables. Given the values for the predictive variables, a sound actuarial assumption can be made for the uncertain variable or event.

Understanding Actuarial Assumptions

An actuarial assumption is an estimate of an unknown value that is determined based on the methods of actuarial science. The process involves using statistical tools to determine the correlation of known values to possible outcomes for the unknown value. Actuarial science is helpful in predicting potential payouts of life insurance policies and pension plans.

An actuarial assumption can include analysis of the following:

Actuarial assumptions are important because they help companies develop contingency plans for the future based on possible outcomes. Actuarial assumptions also allow for the equitable transfer of risk in many situations.

For example, when underwriting life insurance policies, it is important to understand the probability that the insured might pass away during the policy period. Given an accurate actuarial assumption for this probability, a fair premium for such a policy can be calculated. Without the ability to accurately calculate these probabilities, few companies would be willing to provide insurance. If they did offer insurance, it would need to be more expensive to allow room for unexpected losses.

Assumption setting is an essential part of actuarial services across all practice areas–especially as the use of actuarial assumptions continues to rise in the Sarbanes-Oxley era–which was implemented to reduce accounting fraud. The National Association of Insurance Commissioners (NAIC)–a consumer regulatory watchdog–promulgated the Model Audit Rule, which requires, among other things, an independent audit of financial records. Actuarial measurements are often part of financial statements and are an integral part of an organization's risk management practices.

Types of Actuarial Assumptions

One of the most common actuarial assumptions made by insurance companies is the life expectancy projection of a person seeking life insurance. When someone applies for life insurance, an insurance company actuary considers the proposed insured's age, height, weight, gender, tobacco usage, and certain data points relating to their health history. The goal of this type of actuarial assumption is to establish a life expectancy for underwriting purposes.

Although actuarial assumptions are typically used for mortality analysis with life insurance, the same methodologies are also applied to other types of insurance, including liability and property insurance.

In finance, actuaries provide actuarial assumptions for pension plans. Calculations might include the likelihood of investment returns and payout requirements so that a company can plan and account for funding requirements. Actuarial assumptions are also used to determine the level of risk with specific investments. Actuaries who work for investment banks use statistical probabilities to help forecast the financial markets with the goal of reducing risk in an investment portfolio.