Actuarial Assumption Details

Actuarial assumptions involve statistical and mathematical representations designed to evaluate probabilities and risks for a particular event. An actuarial assumption may involve predicting your lifespan given your age, general health, and gender.

To make an actuarial assumption, an actuary will use a table of statistical data that correlates the undetermined variable to a range of essential predictable variables. Given the value of these predictable variables, an actuary can make a reasonable actuarial assumption for the unknown event or variable.

Actuarial assumptions are used to estimate and create financial statements and are often a critical part of an organization’s risk management measures. There are broad applications for actuarial assumptions, including in insurance companies, computer programming, finance industries, and government economic predictions and reports.

Actuarial Assumption Example

Let’s assume that you are seeking a life insurance policy with an insurance company. In this case, the insurer will use common actuarial assumptions used in life policies to project your life expectancy. For your insurance policy, the insurer will look at your age, weight, height, use of tobacco, and general health history to determine your life expectancy and develop a viable policy premium for the insurer and fair for you as the insured.

If, for example, you are a frequent tobacco user looking to buy a $100,000 life insurance policy at the age of 35. Let us also assume that the insurer’s life expectancy is usually 80 years. In normal circumstances, where there are no predicted health risks, the insurer would be counting on 45 years of premium payments. However, in your case, the general assumption is that your tobacco usage is likely to have long-term implications on your health, thereby lowering your life expectancy.

Given your health status, the actuary will use the known variable (your tobacco usage) to estimate the unknown variable (death) and create policy premiums based on this accurate actuarial assumption.

Types of Actuarial Assumptions

The most common actuarial assumption made by insurance companies is the life expectancy forecast when purchasing a life insurance policy. This actuarial assumption aims to determine life expectancy and, consequently, the cost of policy payout for the insurer’s underwriting purpose. Governments and financial planners use economic actuarial assumptions to estimate factors such as inflation, future rates of investment returns, payroll growth, and pay rise growth among plan participants.

In the finance industry, actuarial assumptions are used to estimate the probable cost of pension plans and consequently set the appropriate benefits and contributions. There are two types of post-employment services actuarial assumptions. These include financial and demographic assumptions.

Financial assumptions make estimates around a company’s employee’s fiscal variables such as anticipated salaries and the cost of medical treatment if and when required. Demographic assumptions make estimates about the employee’s characteristics which may include the disability and mortality rate. Other types of actuarial assumptions include the statistical probabilities used by investment banks to forecast the financial market and reduce risk in investment portfolios.

Significance of Actuarial Assumption

Insurance companies use actuarial assumptions to analyze the following:

  • Mortality rates
  • Survivorship
  • Retirement contribution rates
  • Disability rates
  • Morbidity rate, which is the possibility of the occurrence of a disease that would affect a significant portion of the population
  • The probability of the occurrence of catastrophic weather or event

This analysis helps insurance companies predict potential payouts for pension plans and life insurance policies. Actuarial assumptions are also critical in assisting companies in developing contingency plans for the future depending on the possible outcomes. They also allow companies to transfer risks equitably in situations that could be financially disastrous.

For example, when you are purchasing a life insurance policy, it is essential that the insurer fully understands the probability of you (the insured) passing away during the policy period. Based on this accurate actuarial assumption, the insurer will calculate a fair premium for your policy, bearing in mind that you may not live to fulfill your financial end of the bargain. Without the ability to make these actuarial assumptions, insurance companies would be few, and premiums would be expensive to mitigate against the financial risk of unexpected losses.