자동차보험 신뢰도 적용에 대한 베이지안 추론 방식 연구

A study of Bayesian inference on auto insurance credibility application

초록

This paper studies the partial credibility application method by assuming the empirical prior or noninformative prior informations in auto insurnace business where intensive rating segmentation is expanded because of premium competition. Expanding of rating factor segmetation brings the increase of pricing cells, as a result, the number of cells for partial credibility application will increase correspondingly. This study is trying to suggest more accurate estimation method by considering the Bayesian framework. By using empirically well-known or noninformative information, inducing the proper posterior distribution and applying the Bayes estimate which is minimizing the error loss into the credibility method, we will show the advantage of Bayesian inference by comparison with current approaches. The comparison is implemented with square root rule which is a widely accepted method in insurance business. The convergence level towarding to the true risk will be compared among various approaches. This study introduces the alternative way of redcuing the error to the auto insurance business fields in need of various methods because of more segmentations.

키워드

무정보적 사전분포; 베이지안 추론; 부분 신뢰도; 요율 세분화; Bayesian inference; noninformative prior; partial credibility; risk segmentation
제목
자동차보험 신뢰도 적용에 대한 베이지안 추론 방식 연구
제목 (타언어)
A study of Bayesian inference on auto insurance credibility application
저자
김명준; 김영화
DOI
10.7465/jkdi.2013.24.4.689
발행일
2013-08
저널명
한국데이터정보과학회지
권
24
호
4
페이지
689 ~ 699