Munich Re’s Climate Financial Impact Edition
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Munich Re’s
Climate Financial Impact Edition

Visualise the Climate Expected Loss using financial metrics

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    Quantify the financial impact of physical climate risks and bring your analysis and assessment of the physical risks associated with climate change to the next level.

    Climate Financial Impact Edition is an intuitive to use modular SaaS solution, transforming data into clear structures for individual and portfolio risk assessment.

    Building on one of the world’s most comprehensive databases for natural disasters as well as hazard modelling under different climate scenarios, this edition provides detailed information on the physical risk exposure and expected financial impacts of climate change (Climate Expected Loss) for all locations – worldwide. You not only have access to Munich Re’s extensive data collection, but can also incorporate your own data. Integrated into your digital workflows, Climate Financial Impact Edition supports your long-term investment decisions and portfolio steering. Use Climate Financial Impact Edition and benefit from Munich Re’s claims experience when quantifying the potential financial impact of physical risks on your portfolio.

    Climate Financial Impact Edition

    Benefit from the comprehensive Climate Financial Impact Edition

    Easy input & output
    Climate Financial Impact Edition can be accessed via a web application as well as via an API. Because various export formats can be selected, it adapts completely to your needs.
    Easy to interpret visualisation
    Combine with financial information to quantify the real world financial impact of natural hazards on single locations and portfolios.
    Largest global data collection on climate change
    40 years of climate experience and data collection from Munich Re combined with scientific data sets for future-relevant risk scores due to climate change in different RCPs. SSP scenarios will follow in 2023.
    Climate Expert Mode
    Use the future projected financial metrics to anticipate changes in physical climate losses across multiple time horizons and climate scenarios.
    Climate Financial Impact Edition Laptop

    Climate Expected Loss

    Climate Expected Loss (CEL), also known as average annual loss, is the expected loss per year due to physical damage to buildings and their contents resulting from specific natural hazard events.

    The Climate Expected Loss models of the Climate Financial Impact Edition of the Location Risk Intelligence Platform are currently available for the perils of tropical cyclone and river flood, with more perils to follow, for both current and future climatic conditions. The future expected loss reflects the projected altering of the probability and severity of natural hazard events for the different perils at location level, and is available for projection periods 2030, 2050 and 2100, under RCPs (Representative Concentration Pathways) 4.5 and 8.5. With the expected loss being a key metric for risk management, the CEL makes it possible to quantify increased structural losses and repair costs associated with climate change.


    Climate Expected Loss is calculated by combining the expected intensity of a hazard (e.g. flood inundation for river flood or peak wind speeds for tropical cyclones) for each return period within the relevant grid cell, with asset vulnerability curves. These vulnerability curves relate the severity of a hazard event to the expected caused damage, which is expressed as a damage ratio, i.e. the ratio of the cost of repairing the damage to the total cost of replacing the building and its contents entirely (if it is totally destroyed). The vulnerability curves depict the estimated damage to buildings in different parts of the world on the basis of differences in building type, materials and local building codes. This yields the location-specific exceedance probabilities (EP). Climate Expected Loss is the expected value of the modelled loss distribution, which can be seen as the area under the exceedance probability curve.

    Calculating Climate Expected Loss (example: River Flood) 
    Hazard intensity and building vulnerability form the basis for the calculated expected loss
    Calculating Climate Expected Loss (example: River Flood)
    © Munich Re
    High value platform functionalities

    High value platform functionalities

    Sometimes more is simply more. Especially when it comes to well-designed functionalities that facilitate risk assessment on the one hand and reduce your workload on the other. These outstanding functionalities include single location assessment, location geocoding, map services, portfolio assessment, saving of locations, elevation profiles, traffic light visualisation, location set filtering, REST API and areas and lines scoring.

    For further information simply download our “Climate Financial Impact Edition” brochure!

    How about trying our solution right now? Or would you rather talk to someone in person?
    © Myrzik & Jarisch

    How about trying our solution right now?
    Or would you rather talk to someone in person?