How to Research Insurance Companies

Before you complete your insurance, you should understand how insurance companies work. To understand that we have a detailed explanation of the business models of insurance companies based on internet research and talk with some friends who are experts and working in the insurance industry. Let's put the model together in components:

Sign and invest
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Marketing
Sign and invest

Among the raw material conditions, one can say that the business model of insurance companies is to bring more value to premiums and investment income than cost, which is in losses, and at the same time provide a reasonable price that customers will accept.

Yield can be described by the following formula:

result = earned Premium + investment income-incurred loss underwriting costs.

Using these two methods, insurance companies acquire their assets:

Underwriting is the process that insurance companies use to select the insurance risk, and chooses the value of the premiums that will be charged for taking these risks.
To invest the received values in bonuses.
There is a complex side aspect of the business model of insurance companies, which is an actuarial science of pricing based on statistics and the likelihood of the value of future claims under a particular risk. Once the price is set, the insurance company will approve or reject the risks through the underwriting process.

Take a look at the frequency and severity of the insured obligations and the estimated average contribution that ratemaking is at a simple level. What companies do is review all historical data about the losses they have and update them to today's values, and then compare them to the premiums used to estimate the company's interest rate as well as the burden of spending and loss rates. Simply put, we can say that the comparison of losses with loss of Relativitäten is in the way of estimation of different risk characteristics. For example, a double-loss policy should require a double-valued premium. Of course, there is room for more complex computations with multi-variable analysis and parametric computation, where data history is always used because it can be applied to the likelihood of future evaluation losses.