Price optimization procedure is a complex notion. Therefore it uses numerous combinations of various methods and algorithms. Despite the fact that it is still the disputable issue of applying this procedure for insurance, more and more insurance companies adopt this practice.
This process supposes combining the data not related to the expected costs and risk characteristics and the data not related to the expected loss and expenses, and its further analysis. That is, it takes into consideration the changes in comparison to the previous year and policy. Thus, price optimization is closely related to the customers’ price sensitivity.
In other words, historical costs, expenses, claims, risk, and profit are projected into the future. Special algorithms give the insurers the opportunity to adjust the quoted premiums dynamically.
As a key positive feature, price optimization helps to increase the customers’ loyalty in long perspective. Along with this, comes the maximization of profit and income.
