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Analysis on Insurance Policy and Related Customer Behavior using Data Mining Technique

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
M. Ashrafa, D. Asha, D. Radha, M. Sangeetha Priya, R. Jayaparvathy
10.5120/ijca2016909175

M Ashrafa, D Asha, D Radha, Sangeetha M Priya and R Jayaparvathy. Article: Analysis on Insurance Policy and Related Customer Behavior using Data Mining Technique. International Journal of Computer Applications 139(6):46-47, April 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article,
	author = {M. Ashrafa and D. Asha and D. Radha and M. Sangeetha Priya and R. Jayaparvathy},
	title = {Article: Analysis on Insurance Policy and Related Customer Behavior using Data Mining Technique},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {139},
	number = {6},
	pages = {46-47},
	month = {April},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}
}

Abstract

Insurance policy information is not only significant for that particular policy but those features alias contextual information can be utilized for extracting information about those features which are the cause for the cancellation of the policy adoption by the customer. By identifying these features it not only caters to the better understanding of customer behavior but also to create such nonexistent policies based on those features which are not agreed upon for adoption of other former insurance policies. This results in both increased sale of policies and more security for the people by adoption of insurance policies besides the early cancellation of adoption of policies based on certain grounds. In order to reduce dimensionality few salient features which are significant for adoption of policies have been used for the study.

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Keywords

Sum Assured, premium amount, optional rider, risk benefit