Data modeling experience sharing for insurance risk pricing module development

Some time ago in the development of a large insurance company project, among them, involves a risk-priced module, not before the insurance industry, a look at their insurance rate table, suddenly stunned, is a four-dimensional table, that is, four factors (gender, insurance period, payment period, age) to determine a price, There is also a factor affecting the final premium, that is, the amount of insurance (that is---the maximum amount of compensation), but the relationship with the price is linear, draw the mark so here ignore it.

The rates for a certain type of insurance are shown in the following figure:

This is the rate table for some kind of insurance, which is to get a price through four conditions, if a male, the insurance period is set for 30, the payment period is 10, if he is now the age is 14 years old, that his premium price is 22 yuan/year, if is 13 years old, then is 20 yuan/year, this is every million dollars insured amount price, If the insured amount is 100,000 yuan, the premium will be multiplied by the corresponding multiples, resulting in the premium to be supported.

This method of valuation of the different types of insurance, such as the price of the insurance is only related to the period and the period of payment, there is no correlation between sex and age of insurance, in which case the storage in the database will be different, and the formula will not be the same, in addition, not every type of insurance option values are consistent, For example, during the insurance period of this option, a insurance may be 10 and 20 two option values, while the B option may be 30 and to 80 years old, 80 years old three option values, here need enough flexibility, so the data modeling should be considered to support such an application scenario.