Liberty Mutual Re and Celest.Science explore parametric trigger data fallback

Liberty Mutual Reinsurance (LM Re) part of Liberty Mutual Insurance Group, and Celest.Science have announced a collaboration to explore the development of a potential fallback methodology intended to support event characterisation for parametric tropical cyclone insurance when crucial weather data is either unavailable or delayed.

Parametric insurance provides payment when pre-agreed parameters relating to an event, such as a storm’s track, footprint or intensity are met, rather than by reference to assessed loss. However the speed and transparency of this highly depends on having access to trusted sources of data.

With this in mind, LM Re is exploring alternative approaches to ensure data continuity within an evolving risk landscape when access to essential observational inputs is disrupted.

As per the announcement, the collaboration between the two companies will explore how LM Re’s parametric risk transfer expertise and Celest.Science’s climate modelling capabilities can be combined to develop and test a potential missing data methodology.

Celest.Science offers deep levels of expertise in climate intelligence, applying AI, climate physics and advanced modelling to fill gaps where observational data remains limited.

Liberty Mutual Re noted that this collaboration aligns with its broader commitment of working with prominent scientific and technology partners to drive further innovation across its parametric portfolio.

“The proposed methodology would draw on multiple independent data streams alongside advanced physical and statistical modelling to characterise tropical cyclones, even when one or more traditional data sources are unavailable,” LM Re and Celest.Science explained.

The companies further noted that by reducing dependence on any single data source, the proposed approach aims to support confidence, objectivity and operational continuity in event characterisation.

Additionally, the collaboration will assess its potential to strengthen the resilience of parametric insurance and support fast and transparent claims settlement for clients when they need it most.

Importantly, LM Re stated that any future use of the methodology in one of the firm’s products will be subject to successful technical validation, applicable governance approvals and the terms of the relevant insurance or reinsurance contract.

Jean-Christophe Garaix, Head of Parametrics & Agriculture, LM Re, said: “As the risk landscape evolves and the availability of critical observational data becomes increasingly uncertain, LM Re continues to explore innovative approaches intended to enhance the robustness of its parametric products. 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, Celest.Science, said: “Extreme weather often unfolds where observations are fragmented or incomplete. By combining climate science, physics-based modelling and AI, we aim to explore how we can reconstruct a robust picture of what happened. Working with Liberty Mutual Re allows us to explore how that capability could support greater resilience in parametric insurance for end users.

This collaboration between LM Re and Celest.Science is particularly interesting given that parametric catastrophe bonds always have a fallback data provider, or source specified in the bond’s terms. However, with parametric insurance, this doesn’t always seem to be the case.

Therefore, identifying ways to utilise additional data sources to create formal fallback data providers for trigger settlement would be highly valuable for the parametric re/insurance market.