University of Illinois Urbana-Champaign

Improving Business Insurance Loss Models by Leveraging InsurTech Innovation

Quan, Zhiyu; Hu, Changyue; Dong, Panyi; Valdez, Emiliano A.

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A26.pdf

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https://hdl.handle.net/2142/121810

Description

Title
Improving Business Insurance Loss Models by Leveraging InsurTech Innovation
Author(s)
  • Quan, Zhiyu
  • Hu, Changyue
  • Dong, Panyi
  • Valdez, Emiliano A.
Issue Date
2023
Keyword(s)
  • InsurTech
  • Business insurance
  • Loss models
  • Industry and university collaboration
Abstract
Recent transformative and disruptive developments in the insurance industry embrace various InsurTech innovations. In particular, 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 unprecedentedly combine real-life proprietary insurance claims information and its InsurTech empowered risk factors describing insured businesses to create enhanced tree-based loss models. An empirical study in this paper shows that the supplemental data sources created by InsurTech innovation significantly help improve the underlying insurance company's internal or in-house pricing models. The results of our work demonstrate how InsurTech proliferates firm- level value creation and how it can affect insurance product development, pricing, underwriting, claim management, and administration practice.
Type of Resource
text
Genre of Resource
Conference Paper/ Presentation
Language
eng
Handle URL
https://hdl.handle.net/2142/121810

Owning Collections

PSAM 2023 Conference Proceedings PRIMARY