A Novel Intelligence Recommendation Model for Insurance Products with Consumer Segmentation

Xu Wei (), Wang Jiajia (), Zhao Ziqi (), Sun Caihong () and Ma Jian ()
Additional contact information
Xu Wei: School of Information, Renmin University of China, Beijing100872, China
Wang Jiajia: School of Information, Renmin University of China, Beijing100872, China
Zhao Ziqi: School of Information, Renmin University of China, Beijing100872, China
Sun Caihong: School of Information, Renmin University of China, Beijing100872, China
Ma Jian: Department of Information Systems, City University of Hong Kong, Hongkong, China

Journal of Systems Science and Information, 2014, vol. 2, issue 1, 16-28

Abstract: As one of the financial industries, the insurance industry is now facing a vast market and significant growth opportunities. The insurance company will generate a lot transaction data each day, thus forming a huge database. Recommending insurance products for customers accurately and efficiently can help to improve the competitiveness of insurance company. Data mining technologies such as association rules have been applied to the recommendation of insurance products. However, large policyholders’ data will be calculated when it being processed with associate rule algorithm. It not only requires higher cost of time and space, but also can lead to the final rules lack of accuracy and differentiation. In this paper, a recommendation model for insurance products based on consumer segmentation is constructed, which first divides consumer group into different classes and then processed with associate rule algorithm. The empirical results show that our proposed method not only makes the consumption of association rules analysis reduced, it has also got more effective product recommendation results.

Keywords: product recommendation; consumer segmentation; data mining; insurance (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/JSSI-2014-0016 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:2:y:2014:i:1:p:16-28:n:2

DOI: 10.1515/JSSI-2014-0016

Access Statistics for this article

Journal of Systems Science and Information is currently edited by Shouyang Wang

More articles in Journal of Systems Science and Information from De Gruyter
Bibliographic data for series maintained by Peter Golla ().