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Activity Number: 474 - Emerging Methods and Applications in Insurance Data Science
Type: Topic Contributed
Date/Time: Wednesday, August 10, 2022 : 2:00 PM to 3:50 PM
Sponsor: Casualty Actuarial Society
Abstract #320900
Title: Improving Business Insurance Loss Models by Leveraging InsurTech Innovation
Author(s): Zhiyu Quan*
Companies: University of Illinois at Urbana-Champaign
Keywords: InsurTech; business insurance; loss models; industry and university collaboration
Abstract:

Recent transformative and disruptive developments in the insurance industry embrace various InsurTech innovations. Particularly with the rapid advances in data science and computational infrastructure, InsurTech is able to incorporate multiple emerging sources of data and reveal implications for value creation on business insurance by enhancing current insurance operations. In this paper, we unprecedently combine real-life proprietary insurance claims information and features, empowered by InsurTech, describing insured businesses to create enhanced tree-based loss models. Empirical study shows that the supplemental data sources created by InsurTech innovation help significantly improve the underlying insurance company's in-house or internal pricing models. We further demonstrate how InsurTech proliferates firm-level value creation and affect insurance product development, pricing, underwriting, claim management and administration practice.


Authors who are presenting talks have a * after their name.

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