What is it about?
Insurance pricing is traditionally based on expected risk and claims costs. However, insurers also need to understand how customers respond to prices—whether they buy a policy, renew it, or leave when premiums change. This review examines demand-based price optimization in non-life retail insurance. It brings together research on the factors that influence customer demand, the models used to estimate conversion and renewal behaviour, and the methods used to optimize prices. The literature identifies four main approaches: individual optimization, direct ratebook optimization, indirect ratebook optimization, and real-time optimization. The review compares their strengths and limitations and discusses how they can support objectives such as profitability, customer retention, and portfolio growth.
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Why is it important?
Setting insurance prices is a balancing problem. Prices must reflect risk, but they also affect whether customers purchase, renew, or switch provider. Demand-based price optimization helps insurers incorporate these behavioural responses into pricing decisions rather than treating customer demand as fixed. This can support more informed trade-offs between profitability, retention, and growth. The review provides a structured overview of the main methods available and highlights important limitations, regulatory considerations, and areas where further research is needed—particularly for optimizing prices for new business.
Perspectives
Demand-based pricing should not be understood simply as charging each customer the maximum amount they are willing to pay. Its real value lies in understanding how price changes affect customer behaviour and using that information to support broader portfolio objectives. The literature shows that there is no single best optimization method for every insurer. The appropriate approach depends on the available data, how demand is modelled, whether pricing decisions are made at individual or ratebook level, operational constraints, and the regulatory environment. An important future direction is to develop stronger approaches for new-business optimization, where customer behaviour is harder to observe and pricing decisions often need to be made with less historical information.
Prof. Afshin Ashofteh
Universidade Nova de Lisboa
Read the Original
This page is a summary of: Demand-Based Price Optimization in Non-Life Retail Insurance: A Narrative Literature Review, January 2026, Elsevier,
DOI: 10.2139/ssrn.6949510.
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