Developing a Framework for Insurance Underwriting Expert System

نویسندگان

  • Shlomo Berkovsky
  • Yaniv Eytani
  • Edward Furman
  • Udi Makov
چکیده

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.

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تاریخ انتشار 2004