A Concrete Contribution to Managing CatNat Policies, a Legal Requirement for Italian Companies Starting in 2025
Natural disasters in Italy cause billions of euros in damages annually. The year 2023 was particularly devastating, with floods and hailstorms leading to estimated damages between €15 and €20 billion [source: 2024 AON Climate and Catastrophe Insight]. Globally, over the past two decades, the number of major floods has more than doubled, rising from 1,389 to 3,254 (40% of all climate disasters), while the incidence of storms has increased from 1,457 to 2,034 (28%), followed by earthquakes (8%) and extreme temperatures (6%) [source: The Human Cost of Disasters 2000-2019, United Nations, 2020].
The ability to accurately assess natural risks is essential for ensuring adequate protection and mitigating catastrophic damages caused by extreme events.
For this reason, Hypermeteo has expanded its range of high-resolution datasets dedicated to the insurance and risk management sectors, incorporating indices related to CatNat risks such as earthquakes, floods, and landslides. These are integrated with detailed weather and climate information developed over recent years.
Hypermeteo firmly believes that CatNat events like landslides and floods should be assessed within their hydro-geological context, but the meteorological and climatic dimensions must not be overlooked. These events are often triggered by meteorological factors, particularly intense precipitation events. Therefore, their ex-ante evaluation during risk assessment, as well as real-time mapping, is crucial to providing complete and probative information.
The analysis of CatNat risks is made possible by an accurate understanding of the past, utilizing historical datasets of high spatial and temporal resolution (down to 1 km). These datasets are fundamental for analyzing risks under current climate conditions and for making reliable future projections. Future risk assessments based on models that do not rely on representative past data risk being inaccurate and even harmful, as they may produce misleading and inapplicable information.
The use of high-resolution reanalysis datasets has enabled Hypermeteo to create climate scenarios with spatial and temporal resolutions aligned with the demands of the economic sector and the complex topography and climatology of Italy. This allows for tools capable of conducting risk analyses consistent with the taxonomy required by European Union regulators.
