Recommending insurance riders

Lior Rokach, Guy Shani, Bracha Shapira, Eyal Chapnik, Gali Siboni

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Insurance riders are optional addendum to base insurance policies. In this paper we discuss the application of rec-ommender systems to the task of matching riders to clients. This task is difficult because of the variety of possible riders, as well as the poor knowledge of the client over these riders. We focus on call centers where the agent also has limited knowledge and expertise. For such agents, discovering appropriate riders for the current client is very difficult, and automated tools that suggest such riders can play an important role in the agent-client dialogue, and may influence considerably the outcome of the interaction. This paper presents and discusses in detail the problem of recommending insurance riders to clients in call centers, comparing it to other, classic, recommendation system applications. In addition, we present an analysis of customer purchase behavior, showing that simple item-item recommendation algorithms provide good recommendations for riders given a base policy.

Original languageEnglish
Title of host publication28th Annual ACM Symposium on Applied Computing, SAC 2013
Pages253-260
Number of pages8
DOIs
StatePublished - 27 May 2013
Event28th Annual ACM Symposium on Applied Computing, SAC 2013 - Coimbra, Portugal
Duration: 18 Mar 201322 Mar 2013

Publication series

NameProceedings of the ACM Symposium on Applied Computing

Conference

Conference28th Annual ACM Symposium on Applied Computing, SAC 2013
Country/TerritoryPortugal
CityCoimbra
Period18/03/1322/03/13

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