When we talk about the degree of risk in insurance it will always involve a situation because it is related to each other. How could this happen? Because some situations can have a greater risk when compared with other situations.

Back again on risk terms. You must agree how a risk can be measured. When you compare the conditions then you realize that the risks are different. An alternative can lead to “less risk” or “more risk” in a situation.

It is undeniable that generally acceptable levels of risk are directly related to the probability of an event occurring. When you have an intuition that a condition has a higher loss rate it can be concluded that the condition is riskier than other situations.

Thus, to measure the degree of risk we can use the value of probability. Adverse deviations will be the basis for probability. Because as you already know before, the definition of risk is a possible adverse deviation from the results you expect. Thus, the intuitive idea of the degree of risk is consistent with the definition of risk.

Each person would not expect losses. Therefore, the probability of deviating from the desired result when the degree of risk is measured will vary directly with the probability value at which a loss will occur.

## Probability In Degree Of Risk Calculation

We will look at an example of the probability of death at different age levels based on the actuarial life table of American male population by 2014. At age 50, the probability of death for men is 0.004987. Then at the age of 70 years increased to 0.023380. After that, at the age of 90, the probability of death continues to rise to 0.164525.

Here you can see that the probability of death at age 70 is greater when compared with the age of 50 years. However, it is lower when compared with the age of 90 years.

From here it can be concluded that the greater the probability of an event that will occur then the greater the deviation of the expected results. Of course, as long as the loss probability smaller than 1.

There is no chance of loss if the probability of loss is zero and there is no risk. And vice versa, it is not possible when you expect to achieve results where you want it with a probability value of loss 1.

## How Insurance Companies Make Prediction About Losses?

They use estimates to predict the possible losses of a large number of units. Predictions like the above used as a reference to calculate the degree of risk for the insurance clients. Inaccurate prediction is a risk to the insurer.

When clients insure anything then the insurer has a history.

For example, when the insurer estimates 1 in 100 cars will experience a collision and a loss. Thus, if the company guarantees 1,000,000 cars then it is estimated that the car crashed amounted to 10,000 units.

Again, this is just an example of a prediction of a corporate history. Each prediction has a risk that the result may deviate from the expected result.

When the probability value is multiplied by the value of potential losses it will obtain the value of losses expected. For example, if the probability value is 0.2 and the potential loss is $ 1,000 then the expected loss value is $ 200.

As long as these deviations do not incur losses, insurance companies are not at risk. Thus, the premium value paid by insurance policyholders is based on these predictions.