Developing Frameworks for an Insurance Underwriting Expert System

Ehud Makov, Shlomo Berkovsky, Yaniv Eytani

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

Abstract

The process of insurance underwriting determines whether insurance company will accept an application for insurance. It is a complex decision-making process and due to information overload problems, it becomes harder for the insurance companies to efficiently estimate risks in a reasonable time. In this paper we present a framework of an expert system for insurance premium assessment. It combines various Artificial Intelligence techniques, both supervised and unsupervised learning. The proposed framework certainly does not pretend to replace a human underwriter by an electronic one. Rather, it aims at producing viable estimations regarding the clients risk levels, allowing to speed-up the underwriting process and to utilize new potentials
Original languageEnglish
Title of host publicationDatabase and Expert Systems Applications
Pages191 – 197
Number of pages7
StatePublished - 2004

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