{"title":"Towards simplified insurance application via sparse questionnaire optimization","authors":"S. Liu, Guandong Xu, Xiao Zhu, Zili Zhou","doi":"10.1109/BESC.2017.8256362","DOIUrl":null,"url":null,"abstract":"Life insurance application requires in-person meetings with underwriters, tedious paperwork, and an average waiting period of six weeks before an offer can be made. This outdated process has become a barrier for broader consumer adoption, resulting large coverage gap. In this work, we aim to closing this gap by leveraging data mining techniques to optimize the insurance questionnaire form. Our experiment on 10 years of insurance application data has identified that only ∼2% of all questions have shown high relevancy to determining the risks of applicants, resulting a significantly simplified questionnaire.","PeriodicalId":142098,"journal":{"name":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BESC.2017.8256362","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Life insurance application requires in-person meetings with underwriters, tedious paperwork, and an average waiting period of six weeks before an offer can be made. This outdated process has become a barrier for broader consumer adoption, resulting large coverage gap. In this work, we aim to closing this gap by leveraging data mining techniques to optimize the insurance questionnaire form. Our experiment on 10 years of insurance application data has identified that only ∼2% of all questions have shown high relevancy to determining the risks of applicants, resulting a significantly simplified questionnaire.