This paper proposes a conceptual framework to systematize the use of Nature-based solutions (NBS) by integrating their resilience potential into Natural Assurance Scheme (NAS), focusing on insurance value as corner stone for both awareness-raising and valuation. As such one of its core goal is to align research and pilot projects with infrastructure development constraints and priorities. Under NAS, the integrated contribution of natural infrastructure to Disaster Risk Reduction is valued in the context of an identified growing need for climate robust infrastructure. The potential of NAS benefits and trade-off are explored by through the alternative lens of Disaster Resilience Enhancement (DRE). Such a system requires a joint effort of specific knowledge transfer from research groups and stakeholders to potential future NAS developers and investors. We therefore match the knowledge gaps with operational stages of the development of NAS from a project designer perspective. We start by highlighting the key role of the insurance industry in incentivizing and assessing disaster and slow onset resilience enhancement strategies. In parallel we place the public sector as potential kick-starters in DRE initiatives through the existing initiatives and constraints of infrastructure procurement. Under this perspective the paper explores the required alignment of Integrated Water resources planning and Public investment systems. Ultimately this will provide the possibility for both planners and investors to design no regret NBS and mixed Grey-Green infrastructures systems. As resources and constraints are widely different between infrastructure development contexts, the framework does not provide explicit methodological choices but presents current limits of knowledge and know-how. In conclusion the paper underlines the potential of NAS to ease the infrastructure gap in water globally by stressing the advantages of investment in the protection, enhancement and restoration of natural capital as an effective climate change adaptation investment.

Nature-based solutions (NBS) are increasingly being considered as an option to reduce societies’ vulnerability to natural hazards, creating co-benefits while protecting ecosystem services in a context of changing climate patterns with more frequent and extreme weather events. The reinsurance and insurance industries are increasingly cited as sectors that can play a role to help manage risks, by improving disaster risk reduction (DRR) and loss prevention. This paper investigates how the (re)insurance industry could support the transition from a paradigm focused on ex-post responses to ex-ante risk reduction measures including NBS, in line with the Sendai Framework. This paper presents the results of a series of 61 interviews undertaken with the (re)insurance sector and related actors under the EU H2020 Nature Insurance Value Assessment and Demonstration (NAIAD) project. Methods based on a Grounded Theory approach indicate how this sector can play different roles in loss prevention, including ecosystem-based disaster risk reduction (eco-DRR). Results illustrate how the (re)insurance industry, under these roles, is gradually innovating by having a better understanding of hazards and mitigation. The findings of the study contribute to wider discussions such as the possibility of new arrangements like natural insurance schemes and evidence-based assessment of avoided damage costs from green protective measures, in Europe and beyond.

A model has been developed in order to estimate insurance-related losses caused by coastal flooding in France. The deterministic part of the model aims at identifying the potentially flood-impacted sectors and the subsequent insured losses a few days after the occurrence of a storm surge event on any part of the French coast. This deterministic component is a combination of three models: a hazard model, a vulnerability model, and a damage model. The first model uses the PREVIMER system to estimate the water level resulting from the simultaneous occurrence of a high tide and a surge caused by a meteorological event along the coast. A storage-cell flood model propagates these water levels over the land and thus determines the probable inundated areas. The vulnerability model, for its part, is derived from the insurance schedules and claims database, combining information such as risk type, class of business, and insured values. The outcome of the vulnerability and hazard models are then combined with the damage model to estimate the event damage and potential insured losses. This system shows satisfactory results in the estimation of the magnitude of the known losses related to the flood caused by the Xynthia storm. However, it also appears very sensitive to the water height estimated during the flood period, conditioned by the junction between seawater levels and coastal topography, the accuracy for which is still limited by the amount of information in the system.

Wildfires generating damage to assets are extremely rare in France. The peril is not covered by the French natural catastrophes insurance scheme (law of 13 July 1982). In the context of the changing climate, Caisse Centrale de Réassurance—the French state-owned reinsurance company involved in the Nat Cat insurance scheme—decided to develop its knowledge on the national exposure of France to wildfire risks. Current and future forest fires events have to be anticipated in case one of the events threatens buildings. The present work introduces the development of a catastrophe loss risk model (Cat model) for forest fires for the French metropolitan area. Cat models are the tools used by the (re)insurance sector to assess their portfolios’ exposure to natural disasters. The open-source national Promethée database focusing on the South of France for the period 1973–2019 was used as training data for the development of the hazard unit using machine learning-based methods. As a result, we observed an extension of the exposure to wildfire in northern areas, namely Landes, Pays-de-la-Loire, and Bretagne, under the RCP 4.5 scenario. The work highlighted the need to understand the multi-peril exposure of the French country and the related economic damage. This is the first study of this kind performed by a reinsurance company in collaboration with a scholarly institute, in this case EURIA Brest.