Evaluating the New AI and Data Driven Insurance Business Models for Incumbents and Disruptors: Is there Convergence?

Alex Zarifis; Xusen Cheng

doi:10.52825/bis.v1i.58

Authors

Alex Zarifis Loughborough University https://orcid.org/0000-0003-3103-4601
Xusen Cheng Renmin University of China https://orcid.org/0000-0002-5218-4628

DOI:

https://doi.org/10.52825/bis.v1i.58

Keywords:

Artificial Intelligence, Machine Learning, Business Model, Insurance

Abstract

AI and data technologies are a catalyst for fundamental changes to insurance business models. The current upheaval is seeing some incumbent insurers trying to do the same more effectively, while others evolve to fully utilize the new capabilities and users these new technologies bring. At the same time, technologically advanced organizations from outside the sector are entering and disrupting it. Within this upheaval however, there are signs of a convergence towards an ideal and prevailing business model. This research identifies one exemplar incumbent and one disruptor and evaluates whether their models are converging and will become similar eventually. The findings support a high degree of convergence, but some differences are likely to remain even after this transitionary period. The differences identified are firstly in the evaluation of risk and secondly that traditional insurers prioritize revenue generation from what is their primary activity, while new entrants prioritize expanding their user base.

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