Evaluating the new AI and data driven insurance business models for incumbents and disruptors: Is there convergence?
Evaluating the new AI and data driven insurance business models for incumbents and disruptors: Is there convergence?
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.
Artificial Intelligence, Machine Learning, Business Model, Insurance
199-208
Zarifis, Alex
7622e840-ba78-4a4f-879b-6ba0f62363cc
Cheng, Xusen
f88a8aee-cd1d-46f7-8169-8448252003df
2 July 2021
Zarifis, Alex
7622e840-ba78-4a4f-879b-6ba0f62363cc
Cheng, Xusen
f88a8aee-cd1d-46f7-8169-8448252003df
Zarifis, Alex and Cheng, Xusen
(2021)
Evaluating the new AI and data driven insurance business models for incumbents and disruptors: Is there convergence?
Abramowicz, Witold, Auer, Sören and Lewańska, Elżbieta
(eds.)
In 24th International Conference on Business Information Systems.
TIB Open Publishing.
.
(doi:10.52825/bis.v1i.58).
Record type:
Conference or Workshop Item
(Paper)
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.
Text
Evaluating the new AI and data driven insurance business models for incumbents and disruptors Is there convergence Zarifis Cheng 2021
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Published date: 2 July 2021
Keywords:
Artificial Intelligence, Machine Learning, Business Model, Insurance
Identifiers
Local EPrints ID: 490395
URI: http://eprints.soton.ac.uk/id/eprint/490395
PURE UUID: 81a14181-7454-409a-88ef-13512b700977
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Date deposited: 24 May 2024 16:42
Last modified: 06 Jun 2024 02:21
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Contributors
Author:
Alex Zarifis
Author:
Xusen Cheng
Editor:
Witold Abramowicz
Editor:
Sören Auer
Editor:
Elżbieta Lewańska
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