Developing a framework for insurance underwriting expert system

Shlomo Berkovsky; Yaniv Eytani; Edward Furman; Udi Makov

Developing a framework for insurance underwriting expert system

Shlomo Berkovsky, Yaniv Eytani, Edward Furman, Udi Makov

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

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 language	English
Title of host publication	Proceedings of the International Conference on Informatics, ICI 2004
Pages	191-197
Number of pages	7
Publication status	Published - 2004
Externally published	Yes
Event	International Conference on Informatics - Cesme Izmir Turkey Duration: 16 Sep 2004 → 20 Sep 2004

Conference

Conference	International Conference on Informatics
City	Cesme Izmir Turkey
Period	16/09/04 → 20/09/04

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Cite this

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title = "Developing a framework for insurance underwriting expert system",

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 insurancecompanies 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 toreplace 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.",

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AU - Makov, Udi

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N2 - 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 insurancecompanies 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 toreplace 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.

AB - 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 insurancecompanies 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 toreplace 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.

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EP - 197

BT - Proceedings of the International Conference on Informatics, ICI 2004

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