On November 25th, 2025, SCOR and TSE hosted the 2nd workshop on behavioral insurance research. A variety of topics and research methods were presented, and each session was met with animated discussion. In economic literature, behavioral insurance refers to models and empirical studies that integrate insights from behavioral economics into traditional insurance theory, focusing on actual decision-making processes under risk and uncertainty rather than assuming fully rational behavior.

Overview

In considering the application of behavioral science to insurance, we often refer to the insurance journey. This framework tracks the consumer through their dealings with insurance, starting with their Awareness of their need for insurance and their Purchase of an insurance policy, through their experience of Underwriting and their continued Engagement during the life of their policy, and through their Claims experience if they eventually proceed to this stage.  

The presentations in this workshop spanned this journey, providing insights into every stage. To begin, Frédéric Cherbonnier’s presentation on “Optimal insurance for time-inconsistent agents” speaks to the Awareness stage. How do consumers decide if they need insurance in the first place? Cherbonnier’s model reveals that the answer may depend on whether they are time-consistent or time-inconsistent (i.e., have present-biased preferences and lack self-control).(Read the summary)

Nicolas Treich’s presentation on “The (behavioral) economics of pet insurance” also sheds light on the Awareness stage of the journey. This is the first time such insurance market is analyzed in the economic field. Uptake of pet insurance varies widely between countries – could this be due to different levels of awareness around the need for this coverage?(Read the summary)

In the Purchase stage of the insurance journey, Jiakun Zheng presented “Unpacking household insurance decisions: Field and experimental evidence”. This research reveals an asymmetry in the amount of critical illness coverage purchased depending on whether the male or female spouse purchases the insurance.(Read the summary)

When consumers reach the Underwriting stage of the journey, they confront the reality of various risk factors being used to determine their premiums. Charlotte Cavaillé’s presentation on “Everyday moral reasoning and its implications for private insurance markets: A review of the research” shows how consumers evaluate whether specific risk factors (for example zip codes) are fair for insurers to use in their assessments.(Read the summary)

In the Underwriting stage, consumers may also share information about their health status with insurers. Philippe de Donder’s presentation on “Genetic testing with attraction to chance: From pooling to separating contracts” proposes a two-step model to consider consumer attitude to taking a genetic test as well as their attitude to sharing the output of the test with insurers. This provides a framework to consider how availability of genetic testing may impact the sharing of information by consumers at the underwriting stage.(Read the summary)

After the policy is issued, insurers would like to continue reaching policyholders in the Engagement stage. One possibility in this area is policies that incorporate rewards or dynamic premiums based on health information shared from policyholders’ wearable devices. Anthony Vuillaume’s presentation on “Determinants of willingness to share wearables data with insurers: An international analysis” provides insights on the behavioral factors that can explain differences in attitude to sharing wearable data.(Read the summary)

The final stage is Claims, and here François Salanié’s presentation on “Bounded rationality and competition in insurance markets” reveals that consumers are incredibly sensitive to problems at this stage, with non-performance risk having a strong impact on consumer confidence in insurance products.(Read the summary)

Finally, Caitlyn Parsons’s presentation asks “How can behavioral science research help us understand AI in the insurance context?”. AI tools have the potential to transform all stages of the insurance journey, making this an important growing area of research.(Read the summary)

Highlights

This workshop provided new insights into insurance customers’ perspectives:

1. Insurance coverage might differ depending on which spouse is making insurance purchasing decisions within the household
2. Consumers expect premiums to vary based on risk factors, but only those factors that are under personal control are seen as fair
3. Consumers place a value on ‘peace of mind’ in terms of certainty of claim payment and are very sensitive to non-performance risk.

The research sessions uncovered how behavioral factors impact insurance decisions and provide a way of segmenting target audiences to provide tailored financial products. Individuals that value immediate rewards more than future benefits can be described as time-inconsistent and need financial products specifically designed to encourage savings/reduce debt. Emotional attachment to a pet was identified as an indicator of likelihood to take-up pet insurance showing that insurance purchase tends to be not only financially objective (based on an assessment of financial risk associated with vet bills) but also subjective as impacted by emotion. It is expected that individuals’ beliefs about their own health impact their attitude to life insurance but specific measures such as ‘health signal sensitivity’ and ‘knowledge of health’ take this further to identify how well individuals can assess their own health risk and show this as a key driver of demand for insurance and willingness to share information with insurers.

Research methods presented include theoretical models, modelling on survey data, and modelling on insurance data, and each approach brings unique insights. As we look to the future, the variety of research methods provide a toolkit for understanding consumer behavior and how it is changing over time. Measuring consumer attitude to taking a genetic test in terms of whether there is a psychological benefit or a psychological cost associated with taking the test gives an interesting perspective on understanding how availability of genetic testing could impact insurance customer behavior. Consumer attitude to using AI tools and the concept of appropriate trust in these tools will be key factors in determining how the availability of AI tools will impact insurance business.

The breath of research highlights the value that behavioral economics can bring to improve understanding of insurance business. 

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