ImageCat is a risk management innovation company supporting the global risk and catastrophe management needs of the insurance industry, governments, and NGOs. ImageCat develops local, regional, and national “building exposure” databases characterizing the built environment for the purpose of loss estimation- to estimate the financial impacts and cascading effects stemming from natural disasters. ImageCat uses gridded population datasets and other data to extrapolate a portrait of the built environment and uses these data to provide analytics data augmentation services to more accurately characterize risk.
- National building exposure databases: These databases provide organizations with the exposure required to mitigate risk at the national level. National-level exposure databases are developed through a process that combines earth-observation and image processing to identify development patterns with a wide array of site specific data, including virtual reconnaissance, onsite reconnaissance, interviews, and reports.
- Data Disaggregation: Using the exposure databases discussed above, data disaggregation estimates greater detail for aggregated exposures that lack spatial resolution or structural characteristics. These lenses or filters can return a series of possible locations with weights and probable structure type for modeling risk. Available via API.
- Building Valuation: Estimating the magnitude of disruption from natural disasters in financial terms is key to understanding risk both from an insurance and a reconstruction perspective. ImageCat uses an EO-based approach to estimate probable replacement cost, given location and the occupancy of financial assets. Available via API.