What is Actuarial Science?

Introduction

Actuarial science is a method of using mathematics and statistics to try to predict the behavior of financial industries. The discipline requires a great deal of knowledge covering a wide variety of mathematical practices, and is often considered one of the most difficult fields to specialize in. Actuarial science is most often used to try to assess the actions and reactions of the insurance industry and the stock market.

One of the most important functions of actuarial science is to assess risk in a given industry. A qualified actuary is often hired to determine the potential risks and profit margins of opening a new industry, expanding a corporation, or creating new insurance policies. These estimates derive through the use of mathematics and statistical analysis, and require intensive knowledge of finance, economic structures, probability, and computer science. Qualifying as an actuary is understandably incredibly difficult.

Actuarial Science Is A Method Of Statistical Analysis

Used extensively by all facets of the insurance industry. In health insurance, for example, actuaries can create tables that break out mortality rates, population growth, levels of certain diseases, the probability of permanent disability or injury by occupation, and other determining factors that give insurance companies an idea of how high the premiums should be. for profit. These charts can also highlight segments of the population that are at particularly high risk for injuries or illnesses that result in insurance claims, so that the company can adjust rates or provide coverage accordingly.

When Creating Private And Government Pension Plans

Actuarial science is use to determine several critical factors in the implementation and disbursement of pensions. By understanding mortality rates, maximum plan users, and cost-of-living data, actuarial science helps determine who is eligible for the pension, what age it starts, and how the distribution works. This may sound cold-blooded, as if actuaries are trying to figure out when a person will die to save money, but it is a protection against bankrupt or insolvent pension plans, leaving hundreds or thousands of seniors without deserved funds. .

Although concepts such as pensions and insurance have been around since ancient times, it was only with the concurrent development of mathematical and economic theory in the 17th century that actuarial science became commonplace in the business world. Mortality tables were first created in the 17th century, and were quickly use to create the first life insurance policies. Such as those offer by the venerable and still active Society for Equitable Assurances in Lives and Survivors. Know as Equitable Life. This insurance group is credit with coining the term actuary. Which it used to describe its CEO.

The Evolution Of Actuarial Science

Actuarial science needs to be constantly evolving. The market conditions change with the passing of the experiences suffered in times of crisis.

Accessing this information is very difficult. Since each financial company develops its models to find the best results that allow them to obtain the greatest benefits. On the other hand, models must focus on economic reality and not just be based on past evidence. They must anticipate possible future results and situations that may occur in the coming years to cover. Themselves and make the appropriate provisions.

In addition, the models must be deterministic and quantify the volume of risks with well-define. Probability percentages with reduced margins of error.

It should also note that it is essential to identify. Which we the variables that fail in previous financial crises to include them in the financial models.

Currently there is a Great Demand for Actuarial Experts.

This, since companies need professionals with great analytical capacity. To do this, they require engineers, mathematicians, physicists or economists specialized in branches of quantitative economics. All of them, with great knowledge in analysis of all kinds. Especially in the calculation of probabilities of events and risk scenarios.