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  • Kalpesh Agrawal

Application of Actuarial Modelling in Insurance Industry (Part-3)

In the previous two articles, we have discussed the History, importance, and brief overview of Actuarial modeling.

Related: Application of Actuarial Modelling in Insurance Industry (Part-1)
Related: Application of Actuarial Modelling in Insurance Industry (Part-2)

Key Instruments used in Actuarial Modelling

If you have cleared CT5 (CM1) in Actuarial CT series Exams, you must know that A contingent event is an event whose timing, occurrence, and severity is uncertain.

Insurance companies use Actuarial modeling as a risk prediction tool, and in Actuarial modeling, deterministic or stochastic models are used as a key instrument to simply represent the possible future contingent events.


At the time of developing models for insurance companies, different assumptions have been made to make the model reliable. The deterministic model generates the outcomes that seem to be predicted with certainty, but the assumptions taken to generate outcomes are uncertain themselves.


Actuarial models are prepared using an advanced level of mathematical terms and essential Actuarial principles. Bayesian methods are one of the most popular methods, which are used in Actuarial models because in Bayesian methods Actuaries can incorporate prior experience and knowledge at the time of model formulation and estimation.


Insurance companies face various aspects of risk. Actuarial Models contains so many elements which are interrelated assumptions regarding the uncertain risks.


Actuarial Models frequently refined by comparing their results and making changes to the assumptions.


At the time of preparing the Actuarial model, there is a process that reveals how the model is developed from information, theory, and judgment. There are different types of models based on the process used to develop the model. Thompson categorizes models used in Actuarial practice as descriptive models, predictive models, decision-making models, control models, and normative models.


Descriptive models: A descriptive model is the model which describes the historical relationships between the variables modeled.

Predictive models: A Predictive model the model which predicts the future relationships between the variables modeled.

Decision-making models: A decision-making model generates the advice which is given by the actuary to the decision-maker.

Control models: A control model is a fund model, used to develop an objective variable in terms of predictive models and control variables specified by the decision-maker.

Normative models: A normative model shows the choice of a decision-maker between financially risky expectations in terms of data relating to the decision-makers' attitude towards wealth and risk.



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