Towards simplified insurance application via sparse questionnaire optimization

S. Liu, Guandong Xu, Xiao Zhu, Zili Zhou
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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 This outdated process has become a barrier for broader consumer adoption, resulting large coverage gap.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.
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基于稀疏问卷优化的简化保险申请
人寿保险申请需要与保险公司亲自会面,繁琐的文书工作,平均等待六周才能做出报价。这种过时的流程已经成为更广泛的消费者采用的障碍,导致很大的覆盖差距。在这项工作中,我们的目标是通过利用数据挖掘技术来优化保险问卷形式来缩小这一差距。我们对10年的保险申请数据进行了实验,发现只有约2%的问题与确定申请人的风险高度相关,从而大大简化了问卷。
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