Risk-based insurance is a highly debatable question because of its controversial effects on insurance companies and its positive effects on patients. Risk-based insurance depends on the idea of guaranteeing the provisions of the services for clients even if these services’ costs can often exceed the sum of the provided premiums. To predict such situations, it is important to determine the most appropriate premium which is relevant for both the client and the insurance company. Thus, to address society’s demands and to respond to the interest of the insurance company, it is necessary to assess the risks as the basis for calculating the premium, and this assessment depends on several criteria and principles.
Insurance companies calculate premiums with references to risk assessment strategies and tools. To predict the possible risks, it is necessary to focus on the specific demographic information related to the clients, to pay attention to the client’s self-reported health status, and to use data mining techniques in order to research the information about the potential risks. The researched and examined information should be evaluated and assessed with the help of a certain algorithm developed by the specialists of the insurance company in order to address their vision of the correlation between costs and premiums.
The algorithms used for risk assessment work with references to the specific indicators that are necessary to take into consideration while starting the premiums. These indicators often include age, gender, current health status, health risks, characteristics of the lifestyle and job, habits, and hobbies. Risk-based insurance can include additional indicators associated with the concrete sphere. Referring to the indicators, the risks are measured with the help of the developed algorithm. To predict future expenses, it is also possible to use the data on previous years and individuals’ history.
