Fathom’s catastrophe models Our catastrophe models represent tens of thousands of years of synthetic flood events. Used primarily by the insurance and corporate sectors, these sophisticated risk prediction tools are able to model losses, from both frequent and extreme flood events, to build a complete picture of flood risk for a given portfolio of locations.
Financial losses driven by extreme flood events are increasing annually. In a report published by Swiss Re, the reinsurance company identified a combined economic loss of more than $80 billion in 2021. Of these losses only $20 billion were insured. For professionals looking to quantify and manage flood and catastrophe risk, Fathom offers a range of synthetic flood models, that can help to provide efficient solutions to managing risk and engage with regulatory requirements towards climate risk. This includes a range of climate conditioned catastrophe models that can calculated changes in risk for a variety of time horizons.
Increased population exposure to Amphan-scale cyclones under future climates
In 2020 Cyclone Amphan made landfall in the Bay of Bengal and was the first super tropical cyclonic storm to occur in the area in over 20 years. This paper explores what would happen if this event were to occur in the future, asking: would the risks associated with it change?
A 30 m global map of elevation with forests and buildings removed
This work signifies one of the biggest step-changes in global flood modelling capabilities since the advent of the field.
Inequitable patterns of US flood risk in the Anthropocene
Climate change will have major impact on cost of flooding, according to pioneering research led by Dr Oliver Wing, Chief Research Officer at Fathom
Flood Inundation Prediction
This review surveys recent progress made to address fundamental issues surrounding globally consistent mapping of flood hazard in underdeveloped countries. This is achieved through a novel combination of appropriate physics, efficient numerical algorithms, high-performance computing, new sources of big data, and model automation frameworks.
Voluntary purchases and adverse selection in the market for flood insurance
In a wide-ranging analysis in collaboration with Jacob Bradt (Harvard) and Carolyn Kousky (Wharton), we find voluntary insurance purchases are preferentially taking place in areas where Fathom’s model deviates from FEMA flood maps.
An assessment of large-scale flood modelling based on LiDAR data
In this paper we collaborated with colleagues at the University of Concordia to demonstrate the value of bathymetry estimation in large scale model frameworks by testing across four watersheds in Quebec, Canada.