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An Agent-Based Model of Motor Insurance Customer Behaviour in the UK with Word of Mouth

England, R., Owadally, I. ORCID: 0000-0002-0830-3554 & Wright, D. ORCID: 0000-0002-0830-3554 (2022). An Agent-Based Model of Motor Insurance Customer Behaviour in the UK with Word of Mouth. Journal of Artificial Societies and Social Simulation, 25(2), article number 2. doi: 10.18564/jasss.4768

Abstract

Attracting and retaining loyal customers is a key driver of insurance profit. An important factor is the customers' opinion of an insurer's service quality. If a customer has a bad experience with an insurer, they will be less likely to buy from them again. Word-of-mouth networks allow information to spread between customers. In this paper we build an agent-based model with two types of agents: customers and insurers. Insurers are price-takers who choose how much to spend on their service quality, and customers evaluate insurers based on premium, brand preference, and their perceived service quality. Customers are also connected in a small-world network and may share their opinions with their network. We find that the existence of the network acts as a persistent memory, causing a systemic bias whereby an insurer's early reputation achieved by random chance tends to persist and leads to unequal market shares. This occurs even when the transmission of information is very low. This suggests that newer insurers might benefit more from a higher service quality as they build their reputation. Insurers with a higher service quality earn more profit, even when the customer preference for better service quality is small. The UK regulator is intending to ban the practice of charging new customers less than renewing customers. When the model is run with this scenario, the retention rates increase substantially and there is less movement away from insurers with a good initial reputation. This increases the skewness in market concentrations, but there is a greater incentive for good service quality.

Publication Type: Article
Publisher Keywords: Insurance, Word-of-mouth, Agent-based-model, Networks, Customer service, Renewal premium
Subjects: H Social Sciences > HF Commerce
H Social Sciences > HM Sociology
Departments: Bayes Business School > Actuarial Science & Insurance
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