Actuarial science deals with applying quantitative and statistical techniques to answer uncertainties pertaining to the future. It may relate to finance, insurance, or any other field where there is a possibility of loss or injury. Professionals skilled in this field are called actuaries.
In other words, an actuary can be defined as a person having a mathematical crystal ball to look into the future. The creation of the crystal ball (model) requires observations and past experiences. The insights into the future are further finetuned by feeding new experiences and refining any issues in the performance of the model.
History of Actuarial Science
In the 17th century, a need was felt to gain a better understanding of one’s ability to set aside funds for events that are far in the future, contingent on certain events materializing.
The need pertained mainly to the life insurance sector, where the quantum of future liability is known, but the timing is unknown. Thereby, there was a major challenge of discounting backward to know what the present value of the future liability would be.
Using past events, experiences, and learnings, a linear model was devised to answer the question of when in the future the liability would be due. Once the future date is known and the future value is already available, all one needed to do is to discount the future value using a prudent discount rate to obtain how much the company should set aside today to pay for the liability in the future.
Actuarial Science and Modern Finance Theory
Actuarial science was found to be good enough for other applications, including, P&C insurance, auto insurance, pension fund, and recently, criminal justice.
In retrospect, it appears very obvious, but actuarial science can be thought of as the predecessor of modern finance theory. The core tenets of finance, including the time value of money, minimum variance portfolio, and many important axioms, demonstrate connections to actuarial science. Despite the above, no explicit connection existed.
Actuarial Science in the 21st Century
With the advent of modern computers, no one indulges in manual calculation all the time. However, modern computers are undergoing exponential growth in computing power, leading to the automation of many important facets, such as calculation of premiums for term insurance and reserve requirements. Actuaries are getting with more opportunities to use their expertise in more complex and related uses, such as asset allocation models.
Applications of Actuarial Science
1. Life insurance
Suppose an insurance broker is evaluating what is the price to be charged for a plain vanilla term insurance to a 25-year-old client and a 40-year-old client. In the above situation, there are several variables involved, i.e., the current health of the client, expected lifespan, lifestyle choices, etc. So, it’s not humanly possible to do a quick calculation to come up with a price. This is where the genius of the actuary becomes useful.
The actuary is able to access historical data across genders, age groups, and various other strata. Using a complex mathematical model, the actuary can estimate the probabilities of survival for each of the strata. All that remains is putting the client in the appropriate strata, thereby obtaining how risky the client is to insure.
Let’s assume the probability of death is 2% for the 25-year-old and 8% for the 40-year-old. In both cases, the sum insured is $100,000. Therefore, the premium charged would be 2% of $100,000 and 8% of $100,000, respectively.
2. Health insurance
Let’s suppose a healthy person who is 30 years old needs to be insured. Now, the analysis must also focus on the type of occupation a person does, the probability of disability, and other contingencies. A variation of the life insurance model would be deployed to arrive at the premium to be charged.
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