What is Actuarial Science? Definition of Actuarial Science, Actuarial Science Meaning and Concept
The science actuarial studies financial risks and insurers through complex algorithms and mathematical models. These interpret the functioning of the economy through the probability of the occurrence of certain events.
Actuaries are well acquainted with information technology and risk management systems, as well as the variables included in financial models and the tests carried out under stressful situations.
The models have to be realistic and with a very high success rate. In addition, the forms of action must be defined, in case the forecast fails, and the protocols that allow facing complex situations outside the proposed scenarios.
Therefore, constant analytics and stress tests are essential for this science, as well as investment in technology that allows access to information from complex networks where the models are made up of multiple variables that must be taken into account.
The Evolution of Actuarial Science
Actuarial science needs to be constantly evolving. This, since market conditions change with the passing of experiences in times of crisis.
Accessing this information is very difficult, since each financial company develops its own models in order 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 evidence from the past. Thus, they must anticipate possible future results and situations that may occur in the coming years to cover themselves and make the appropriate provisions.
Furthermore, the models must be deterministic and quantify the volume of risks with well-defined probability percentages with low margins of error.
It should also be noted that it is essential to identify which were the variables that failed 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 skills. For this, they require engineers, mathematicians, physicists or economists specialized in branches of quantitative economics. All of them, with great knowledge in matters of analysis of all kinds, especially in calculating the probability of events and risk scenarios.