To decide how much an insurance policy should cost a customer, underwriters use: Data analytics.
Data analytics can be defined as the systematic computational collection, modelling and analysis of raw data, in order to discover trends, patterns, and draw conclusions about the information that are contained in the data.
An insurance policy can be defined as a contractual agreement between an insurer and an insured (policyholder), in which the claims, terms and conditions binding on both parties are listed in details.
Thus, it is a contract in which an insurer indemnifies an insured (policyholder) against losses in the event of certain dangers or problems.
Underwriting refers to a process through which an insurer determines the risks of insuring a customer and establishing the required cost (price).
Basically, underwriters use data analytics to predict risk levels and determine how much an insurance policy should cost a particular customer. Some examples of the data used by underwriters are:
- Historical industry trends.
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