文章基本信息

标题：Predictive Modelling for Motor Insurance Claims Using Artificial Neural Networks
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作者：Zuriahati Mohd Yunos ; Aida Ali ; Siti Mariyam Shamsuddin 等
期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2016
卷号：8
期号：3
出版社：International Center for Scientific Research and Studies
摘要：The expected claim frequency and the expected claim severity areused in predictive modelling for motor insurance claims. There are twocategory of claims were considered, namely, third party propertydamage (TPPD) and own damage (OD). Data sets from the year 2001to 2003 are used to develop the predictive model. The main issues inmodelling the motor insurance claims are related to the nature ofinsurance data, such as huge information, uncertainty, imprecise andincomplete information; and classical statistical techniques whichcannot handle the extreme value in the insurance data. This paperproposes the back propagation neural network (BPNN) model as a toolto model the problem. A detailed explanation of how the BPNN modelsolves the issues is provided
关键词：predictive modelling; claim frequency; claim severity; back;propagation neural network