Introduction

Climate change is reshaping our world, impacting industries far and wide. For insurers, understanding the risks posed by climate-related events is essential. By analyzing exposure and losses, insurers can better assess risk, allocate resources wisely, and develop strategies to navigate the challenges ahead.

In this presentation, we explore the complex world of insurance, focusing on market insurance exposure and loss data derived from a subset of insurance companies in the European Region.

‘Exposure’ refers to the overall value or replacement value of insured residential and commercial buildings. Conversely, ‘loss’ refers to incurred claim amounts reported by insurance entities, providing insights into the financial impacts of climate events.

Data

• The time series data from National Centers for Environmental Information (NOAA), gives us an overview of climate change globally vs in Europe since 1911.

• The data from the European Insurance and Occupational Pensions Authority (EIOPA), helps us understand the materiality of the European insurance sector’s exposure to climate-relevant perils and assess the potential impact of physical climate change risk. Our sample includes Sum Insured and Losses from 35 major European groups actively engaged in non-life business, alongside nine non-life and composite solo undertakings with significant exposure to property damage. It’s essential to note that these figures do not represent a 100% view of the entire market, but rather offer valuable insights into the sector’s response to climate-related risks.

• A shapefile from Eurostat is used to visualize exposure and loss information on the European map, with added interactivity to examine values for each country in a single visualization.

Average Temperature Anomalies: Global vs Europe (1911-2024)

• The provided time series graph illustrates the average temperature anomalies globally and in Europe, over a period spanning from 1911 to 2024.
• Both global and Europe temperature anomalies exhibit an upward trend. This indicates a gradual increase in temperatures during this timeframe. Europe’s temperature anomalies have consistently been higher than the global average. Potentially due to urbanization, geographic location etc.
• Rising temperatures have significant consequences for various sectors, including insurance. Insurers must consider these trends when assessing risks and designing climate-resilient policies. Let’s take a look at the European Insurance markets exposure and loss in further slides.

Flood and Windstorm Insured Exposure in Europe

• The interactive choropleths below visualizes the Total Sum Insured (Value of buildings after deducting reinsurance and coinsurance) in each country by peril for 2020. Dark red indicates a high sum insured. Hover over Countries to check exposure values.
• The majority of exposures are concentrated in Germany, France, and Spain. Spain has the highest flood exposure, while Germany has the highest windstorm exposure. This distribution is logical given these countries’ economic size, susceptibility to natural disasters, and population density. Let’s take a closer look in the next slide.

Top Exposed Countries to Climate Perils

• This chart again illustrates the Sum Insured by Country for each peril, highlighting the insured values clearly. Germany has the highest sum insured across both perils, totaling 8.9 trillion.

• Additionally, there are tables provided that display the top 3 sum insured values for each peril.

Detailed Exposure Analysis at NUTS (Nomenclature of Territorial Units for Statistics) Level

• The bar chart below provides insights into the top 10 exposure values across the territories of each country.
• It appears that the majority of exposure is concentrated in Spanish territories for both perils. However, these represent only the top 10 territorial losses, and in terms of overall exposure, Germany remains the country with the highest concentration, as noted earlier.
• Notably, the exposure values are largely identical between the two perils, suggesting that these are likely the same policies that include both flood and windstorm coverage.

Insurance Loss from Major Climate Events in Europe

• The interactive (Hover over plot) choropleth below visualizes the insurance losses accumulated from three major catastrophic events in Europe i.e. Windstorm Ciara Feb.2020, WildFire Portugal 2017, Flood May/June 2017.
• It is evident that Germany has incurred the highest loss, approximately 1.5 billion EUR, compared to other countries. This aligns with the trend in exposure, where Germany also had the highest insured values.

Country-Level Insured Losses by Peril

• Flood in June 2013 affected Czechia, Germany, Switzerland, Hungary, and Austria. This event was one of the most expensive flood events in Europe since 1980, with estimated losses between EUR 11.7 billion and EUR 16 billion, of which only EUR 2.4 to 3.8 billion were insured. Germany was the most affected, incurring the highest losses across all perils.
• Windstorm Ciara struck large parts of central Europe in early February 2020. It was among the costliest natural disasters in Europe in 2020, causing an estimated insured loss of EUR 1.6 billion. Germany experiencing the highest insured losses.
• The 2017 wildfire event primarily affected Portugal. This event is considered the deadliest wildfire in Portugal’s history and the most severe wildfire ever recorded in Europe.
• Again, the below does not contain 100% market view, so the actual losses will be higher.

  Data Source: EIOPA.(n.d). https://www.eiopa.europa.eu/document/download/50e6b095-174c-4d9c-b9dd-1376dc1d43eb_en?filename=Historical%20loss%20data.xlsx

Summary and Conclusion

The presentation focuses on climate change and its economic impact on regions like Europe. As the fastest warming continent, Europe faces numerous climate-related catastrophes, leading to significant economic losses for both policyholders and insurers. Insurers heavily invest in high-risk countries, necessitating careful policy structuring with appropriate deductibles, limits, or higher premiums to mitigate financial damage. Below are a few additional future directions.

Future Directions

• Urgency of Climate-Resilient Policies: With rising temperatures and more frequent climate-related claims, insurers must develop climate-resilient policies. This means updating risk models to handle the increasing severity of climate events.

• Importance of Geographic-Specific Strategies: High exposure and losses in specific European countries highlight the need for customized strategies that address unique regional climate risks.

• Need for More Historical Data: The current dataset has limitations where it is not showing a full view of the event. Expanding the dataset to include more insurers and detailed geographical information is important. This will lead to more accurate risk assessments and better decision-making.

• Public Awareness and Education: Educating policyholders about climate resilience can significantly reduce overall risk. Through educational campaigns and incentives, insurers can help create a more prepared society.

By addressing these future directions, the insurance industry can better navigate the challenges posed by climate change, ensuring long-term stability and protection for both insurers and policyholders.

References

• European Insurance and Occupational Pensions Authority. (n.d.). Catastrophe data hub. EIOPA. https://www.eiopa.europa.eu/tools-and-data/catastrophe-data-hub_en
• European Insurance and Occupational Pensions Authority. (n.d.). Catastrophe data hub: Flood and Windstorm exposure data - catastrophe data hub. EIOPA. https://www.eiopa.europa.eu/document/download/d2be6f79-3e44-47f1-821f-97ff41e9d7b6_en?filename=Flood%20and%20Windstorm_exposure_data.xlsx
• European Insurance and Occupational Pensions Authority. (n.d.). Catastrophe data hub: Historical loss data - catastrophe data hub. EIOPA. https://www.eiopa.europa.eu/document/download/50e6b095-174c-4d9c-b9dd-1376dc1d43eb_en?filename=Historical%20loss%20data.xlsx
• National Centers for Environmental Information. (n.d.). Climate at a glance: Global time series. NOAA. https://www.ncei.noaa.gov/access/monitoring/climate-at-a-glance/global/time-series/globe/land/12/4/1911-2024
• National Centers for Environmental Information. (n.d.). Climate at a glance: Global time series. NOAA. https://www.ncei.noaa.gov/access/monitoring/climate-at-a-glance/global/time-series/europe/land/12/4/1911-2024
• Eurostat. (n.d.). Geodata: Territorial units for statistics. European Commission. https://ec.europa.eu/eurostat/web/gisco/geodata/statistical-units/territorial-units-statistics
• United Nations. (2023, June 6). Europe warming twice as fast as other continents, warns WMO. UN News. https://news.un.org/en/story/2023/06/1137867
• Stack Overflow. (2017, November 8). R markdown and plotly fig.align not working with HTML output [Online forum post]. https://stackoverflow.com/questions/47193192/r-markdown-and-plotly-fig-align-not-working-with-html-output
• Baptiste Auguie (2017). Displaying tables as grid graphics. The Comprehensive R Archive Network. https://cran.r-project.org/web/packages/gridExtra/vignettes/tableGrob.html