Natural hazard losses are sensitive to the dependency between extreme values of the hazard variable at different spatial locations. It is therefore important to correctly identify and quantify dependency to accurately model the hazard and its resulting losses. Through application to a large data set of windstorm hazard footprints, this study demonstrates how extreme-value methods can be used to explore extremal dependency and hazard losses in very high dimensional natural hazard data sets.