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An agent-based system with temporal data mining for monitoring financial stability on insurance markets

Owadally, M. I ORCID: 0000-0002-0830-3554, Zhou, F., Otunba, R., Lin, J. and Wright, I. D. (2019). An agent-based system with temporal data mining for monitoring financial stability on insurance markets. Expert Systems with Applications,

Abstract

We describe an expert system to monitor the stability of insurance markets. It consists of two components: an agent-based simulation component and a temporal data mining component. Like other financial markets, insurance markets experience destabilizing cycles and suffer episodic crises. The expert system assists market regulators by monitoring the financial position of individual insurers and of the overall market, and by forecasting cycles and impending insolvencies. The agent-based simulation component runs a forward simulation allowing for interaction among insurers in a competitive market, and between insurers and customers. The temporal data mining component extracts useful information for market regulators from the simulations. A prototype of the system is applied to the automobile insurance market. We show how the system may be used to forecast cycles, investigate stability, and analyze insurers’ herding behavior on the market. A practical policy conclusion is that regulators should monitor individual insurers’ pricing pattern because aggressive price undercutting creates a “winner’s curse”, with subsequent losses and market instability.

Publication Type: Article
Additional Information: © Elsevier, 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords: Agents, Motif, Anomaly, Cycle, Crisis, Automobile insurance
Subjects: H Social Sciences > HG Finance
Departments: Cass Business School > Actuarial Science & Insurance
URI: http://openaccess.city.ac.uk/id/eprint/21275
[img] Text - Accepted Version
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