<div>Climate change is increasingly recognized as a top global threat impacting human, environmental, and economic systems.</div><div>When it comes to property & casualty insurance risk, AXA considers every aspect of the risk equation.  As far as natural catastrophes risks are concerned, climate risk is a function of (i) the physical hazard (the severity and frequency of events); (ii) the exposure (the monetary value of insured asset(s)) and (iii) the vulnerability (the susceptibility or damageability of the insured asset(s) to a given hazard intensity). Each of these elements plays a unique role in driving climate risk both now and into the future. The changes AXA see in its year-on-year losses from climate-linked hazards are a function of all risks components and not just the hazard, which is a common misconception.</div><div>AXA is developing internally Natural Hazard models (or Natural Catastrophe models) to estimate the climate risk damages and losses to individual risks or (re)insured portfolios.</div><div>To perform forward looking analysis, AXA identified different complementary approaches that could be envisaged to assess the future of natural hazards risks according to both the peril and region combinations AXA has exposure to as the availability and quality of data for the three drivers of the risk. Those approaches have been notably used for several regulatory climate stress tests AXA was involved in.</div><div>One of them is a global proportional approach simple to implement to consider at a large scale the evolution of hazard, exposure, vulnerability impacts on climate risk for long term time horizons and several warming scenarios. The model is built on current science knowledge related to climate change.</div><div>A more sophisticated approach for local-scale assessment is currently being developed. It consists in integrating in the Natural Hazard models a modified view of hazard (stochastic events catalogue) / exposure / vulnerability capturing forward-looking scenarios. AXA is currently upgrading all its Natural Hazard models in that direction. AXA Europe Flood risk model is for instance assessing future of fluvial and pluvial risks from modified precipitation datasets representative of future warming scenarios. Future precipitation are made of baseline current precipitation from which a “delta” precipitation is added, based on CMIP6 temperature anomalies and Clausius-Clapeyron scaling. Hydrological and hydraulic models are then run using this new future precipitation datasets to generate stochastic flood events catalogue for future warming scenarios risks assessment.</div><div> </div><div> </div>

<p>AXA proposes a novel continental-scale generator of synthetic gridded rainfall daily timeseries (10km resolution) with applications to cross-country risk assessment under current and future climate scenarios. Europe serves as a case-study to demonstrate and assess its performance in terms of hazard modelling and extrapolation to unobserved extreme local and regional events. This generator belongs to the class of time and space reshuffling Stochastic Weather Generators (SWGs) and generates unobserved events by re-sequencing historical multisite timeseries (E-OBS). Consistency at continental scale is ensured by relying on weather regimes and atmospheric situations characterized from the ERA5 reanalysis over Europe. The use of atmospheric drivers and dry-wet alternating cycles allows for the determination of both precipitation-prone situations or on the contrary drier spells, while preserving the physics of the atmospheric water cycle. Spatial reshuffling is introduced by regional differentiation. Transitions between regimes can be either calibrated from the historical data or extrapolated to represent future states of the climate along with an appropriate uplifting of the humidity-related variables. This generator is operationally used at AXA as part of a European flood risk model and serves as the main input to an hydrological and hydraulic model.</p>

<p>The insurance industry faces highly complex P&C challenges, among which natural catastrophe risk, also labeled as “CAT” risk. Among disasters, climatic and seismic events show large variability in size and frequency, with devastating consequences; not to mention climate change which brings added uncertainty for the future. Global insurance groups, such as AXA, must develop a sound understanding of the frequency, intensity, and impacts of natural hazard events, to protect their economic capital and ensure their solvency.</p> <p>At the AXA Group Risk Management, the CAT modeling process consists in 1) collecting CAT exposure data (geographical, physical, and financial information) on a per-entity (AXA France, AXA Mexico…) and per-location basis (houses, factories, vehicles…) and 2) assessing the risk on a per-entity per-peril per-geography basis (cyclones, earthquakes, floods, hailstorms...) to finally aggregate it at Group level. This process constitutes a technical challenge through the data collection of 50 million of policies, the combination of multiple modeling solutions, and the production of millions of stochastic event losses. Alongside this process, the collection and analysis of “scenarios”, either historical events, or potential future disasters, improves the robustness and understanding of risk assessment. However, there is currently no unified and consistent database recording the characteristics of natural events (a unique identifier, their spatial and temporal extent, their intensities, and the location affected) and their actualized economic and industry impacts. This work aims at developing a database for that would first gather an exhaustive inventory of historical natural events (cyclones, storms, floods, earthquakes…) and, throughout the integration within the existing CAT modeling ecosystem, automatize model validation, back-testing, and risk analysis with respect to market and as-if losses. </p>

<p>The flood event “Berndt” in North-Western Europe in July 2021 demonstrated to stakeholders the critical importance of understanding present-day events, their spatial-temporal coherence and magnitude, and the probability of their occurrence. The shear size of multi-country events such as “Berndt” necessitate a large scale and highly automated approach to the modelling of their characteristics.</p> <p>To this end, we (AXA, Fathom and Deltares) developed a modelling framework that can efficiently compute very large event sets and worked on improving its underlying skill by making the framework highly modular. The framework consists of the following modules: a synthetic weather generator, which may sample many thousands of years of continuous weather data at daily and sub-daily time scales; a gridded hydrological model forced by the synthetic weather that produces long-term hydrological timeseries and derived statistics, and a subcatchment-scale fluvial and pluvial flood model archive, produced from large amounts of simulations with the Fathom hydraulic flood model engine. Its modular character allows for exchanging components, improving existing components or modifying parameters to assess sensitivities or uncertainties.</p> <p>In last year’s contribution, we presented our first synthetic simulations of weather and hydrology. In this year’s contribution we have improved stochastic weather generation and have established a full 10,000-year event set and flood catalogue, both under the present climate and a future climate projection that encompasses several assumptions. We will show the statistics and spatial configuration of past events according to our catalogue, including “Berndt 2021”, and how the statistics of extreme events will change according to the defined climate scenario simulation.</p>

<p>European windstorms are powerful extratropical cyclones mostly taking place during the winter months, and are one of Europe’s costliest natural disasters. The close study and assessment of this risk has therefore been essential for the insurance industry concerned. Typically, insurers resort to physical natural catastrophe models developed by third-party companies to analyze the risk, as they capture its components of hazard (events frequency and severity), exposure (insured assets values), and vulnerability (assets' damageability to given hazard intensities). AXA proposes a modeling methodology to produce a hazard catalog of synthetic windstorm events, and a vulnerability module, built around publicly available, purchased, or internal data. The hazard catalog is created using a meteorological feature tracking algorithm to extract trajectories and footprints of European windstorms in CMIP6 and ECMWF-ERA5 data. The catalog is then enriched to become a 10,000-year stochastic catalog by physically resampling original events with a perturbation technique, and statistically downscaling them to a 4-km resolution. The vulnerability, that yields damage ratios from local windspeed intensities, predicts the expected probability of claim occurrence and a distribution of conditional damage ratios based on wind gust value and exposure risk drivers. The model shows good backtesting performances at continental scale on market and AXA exposure. It is fully integrated within AXA's modelling ecosytem and is operationnally used to assess one of the major risks faced by the Group. </p>