Liberty Mutual Reinsurance (LM Re) has joined forces with Celest.Science to develop a new fallback methodology aimed at enhancing event characterization for parametric tropical cyclone insurance. This initiative addresses challenges that arise when critical weather data is unavailable or delayed, potentially impacting the transparency and speed of claims processing.
Parametric insurance provides payouts based on predefined parameters of an event, such as the intensity or track of a storm, rather than assessed losses. The effectiveness of this model relies heavily on trusted data sources, which can be disrupted in changing risk environments. In response, LM Re is seeking innovative approaches to ensure data continuity.
The partnership will leverage LM Re’s expertise in parametric risk transfer and Celest.Science’s advanced climate modeling capabilities to create and test a methodology designed for situations where conventional data sources fail. Celest.Science specializes in climate intelligence, utilizing artificial intelligence and advanced modeling techniques to address gaps in observational data.
According to both companies, the proposed methodology aims to incorporate multiple independent data streams in conjunction with physical and statistical modeling to accurately characterize tropical cyclones, even in the absence of traditional data sources. This approach seeks to reduce reliance on any single data provider, thereby promoting confidence and operational continuity in event characterization.
The collaboration is expected to enhance the resilience of parametric insurance and facilitate faster, more transparent claims settlements for clients during critical periods. Any future application of the developed methodology in LM Re’s products will depend on successful technical validation and adherence to applicable governance and contractual terms.
Jean-Christophe Garaix, Head of Parametrics & Agriculture at LM Re, emphasized the importance of timely funding access for clients during natural disasters, stating, “When a tropical cyclone strikes, our clients need timely access to funds so they can focus on recovery. Our collaboration with Celest.Science enables us to explore options that could provide that extra layer of resilience, even if a primary data source becomes unavailable.”
Léo Lemordant, Co-Founder and CEO of Celest.Science, added, “Extreme weather often unfolds where observations are fragmented or incomplete. By combining climate science, physics-based modeling, and AI, we aim to explore how we can reconstruct a robust picture of what happened.”
The partnership is particularly timely as the need for formal fallback data providers is increasingly recognized in the parametric reinsurance market, potentially offering significant value through enhanced data utilization.
