Actuarial Risk

Actuarial risks are the risks that the assumptions that actuaries implement into a model to price a specific insurance policy may turn out wrong or somewhat inaccurate. Possible assumptions include the frequency of losses, severity of losses and the correlation of losses between contracts. Actuarial risk is also known as "insurance risk."

The level of actuarial risk is directly proportional to the reliability of assumptions implemented in pricing models used by insurance companies to set premiums.

Life, in general, carries many risks. For example, a homeowner faces a large potential for variation associated with the possibility of economic loss caused by a house fire. A driver faces a potential economic loss if his car is damaged. A larger possible economic risk exists with respect to potential damages a driver might have to pay if he injures a third party in a car accident for which he is responsible. A major part of an actuary's job is to predict the frequency and severity of these risks as they relate to the financial liability for risks taken on by an insurer in an insurance contract.

Actuaries use various types of prediction models to estimate risk levels. These prediction models are based on assumptions, and ensuring those assumptions in a model actually reflect real life is vital for the pricing of all types of insurance. Flaws in a model's assumptions could lead to premium mispricing. In the worst case scenario, an actuary may underestimate the frequency of an event. The unaccounted incidents will cause an increase in the frequency of payouts, which could bankrupt an insurer.

One of the most common risk assessment models – and thus actuarial risk – are life tables, which are used to price life insurance policies. Life tables seek to predict the probability that a person will die before his or her next birthday. There are two primary types of life tables used in modern actuarial science – period life tables and cohort life tables.

A period life table represents mortality rates during a specific time period of a certain population. A cohort life table, often referred to as a generation life table, represents the overall mortality rates of a certain population's entire lifetime. For a cohort life table, a population must have been born during the same specific time interval. A cohort life table is more frequently used because it is able to make a prediction of any expected changes in mortality rates of a population in the future. This type of table also analyzes patterns in mortality rates that can be observed over time. Both of these types of life tables are created based on an actual population from the present, as well as an educated prediction of the experience of a population in the near future. However, as the weight given to "educated predictions" in a life table increases, the more actuarial risk will be involved with writing insurance policies based on those predictions.

Life tables may also be based on historical records, although these often undercount infants and understate infant mortality, on comparison with other regions with better records, and on mathematical adjustments for varying mortality levels and life expectancies at birth. The reliability and completeness of those historical records also affect the actuarial risk of such calculations.