Abstract
When an insurance company calculates the premium it will divides the policy holders into groups. The division is considered based on risk level in each group. The problem is then to devise a way of combining the experience risk of the group with the experience of the individual risk to calculate the premium, so then Credibility Theory provides a solution to this problem.This script discuss about calculation of credibility premium use Buhlmann-Straub Model with nonparametric estimation to the aggregate claim amount data set within few years observation in some group of policy holders in general insurance. By using credibility theory we can calculate the value of credibility factor and credibility premium or future premium. The value of premium credibility is calculated from only one group of policyholders from the previous year's data. For better value of premium credibility, data with more experience years and the policyholder group better reflect the total loss value during the observation year.The result of this calculation are credibility factor per group, average credibility premium per members in group and credibility premium total for the last year for each group. We can obtain total losses and total premium which surprisingly equal.
Highlights
At this time the general public began to realize the need for protection from other parties against losses or accidents that they might experience, so insurance companies took that role (Chantarat 2013; Clement, 2018)
By paying premiums in each particular payment period to the guarantor in accordance with the policy that has been purchased, the insurance participants will get coverage from the insurance company when they have submitted a claim for loss / accident they experienced (Budd, 2004; Ranasinghe, 2019)
Some people or organizations who buy insurance know that they have a tendency to make claims that are greater than the insurance company's trust in them
Summary
At this time the general public began to realize the need for protection from other parties against losses or accidents that they might experience, so insurance companies took that role (Chantarat 2013; Clement, 2018). In many cases the amount of data available is too small to make a conclusion about the differences above or about the possibility of an extension of these differences. This brings us to the notion of credibility (Kim, 2013). This paper will describe and explain the problem of premium credibility in loss insurance using the Buhlmann-Straub model with nonparametric estimates and determine the level of credibility from the previous claim data. The credibility of the premium is useful for insurance companies to determine the insurance premium and increase the accuracy of the premium seen from the experience of previous years
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