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 This outdated process has become a barrier for broader consumer adoption, resulting large coverage gap.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. Copyright © 2017 IEEE.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 4th International Conference on Behavioral, Economic, and Socio-Cultural Computing, BESC 2017 |
| Editors | Yves DEMAZEAU, Jianbo GAO, Guandong XU, Jarosâaw KOĨLAK, Klaus MÜLLER, Imran RAZZAK, Hao CHEN, Yanhui GU |
| Place of Publication | Danvers, MA |
| Publisher | IEEE |
| ISBN (Electronic) | 9781538623657 |
| DOIs | |
| Publication status | Published - 2017 |