Abstract: In an illustrative embodiment, an automated system performs a multi-level risk exposure analysis for geographic locations, such as property locations. The system may include computing systems and devices for calculating, for locations in a portfolio, risk exposure amounts for an area that includes an insured location and including an analysis radius and identifying regions of interest having risk exposure amounts that exceed predetermined amounts due to combined exposure from a portion of the insured locations. The system may generate a grid of intermediate points that is applied to each region of interest. The system may calculate amounts of risk exposure for each of the intermediate points and retain any intermediate points with risk exposure amounts that exceed the amounts for the insured locations. The system may output a risk exposure analysis based on the risk exposure amounts for the insured locations and intermediate points of interest.

Abstract: In an illustrative embodiment, systems and methods for determining exposure include detecting, based on received data from external entities, an occurrence of a catastrophic event. Responsive to detecting the occurrence, a first matrix is generated indicating features of one or more properties within a vicinity of the catastrophic event, and a second matrix is generated representing characteristics of the catastrophic event. Using the first matrix and the second matrix, a convolution calculation matrix is calculated indicating amounts of correspondence between the first matrix and the second matrix. In real time, in response to detecting the occurrence of the catastrophic event, risk exposure information is presented to at least one remote computing system associated with at least one property of the plurality of properties, where the risk exposure data relates to the amount of correspondence between the first matrix and the second matrix in reference to the at least one property.

Abstract: In an illustrative embodiment, systems and methods for determining exposure include detecting, based on received data from external entities, an occurrence of a catastrophic event. Responsive to detecting the occurrence, a first matrix is generated indicating features of one or more properties within a vicinity of the catastrophic event, and a second matrix is generated representing characteristics of the catastrophic event. Using the first matrix and the second matrix, a convolution calculation matrix is calculated indicating amounts of correspondence between the first matrix and the second matrix. In real time, in response to detecting the occurrence of the catastrophic event, present risk exposure information to at least one remote computing system associated with at least one property of the plurality of properties, where the risk exposure data relates to the amount of correspondence between the first matrix and the second matrix in reference to the at least one property.

Abstract: Systems and methods of the present technology provide the capability to determine risk exposure of points of interest (e.g., insured locations) based on the occurrence of an event (e.g., a catastrophic event). The systems and methods use two-dimensional convolution and FFT processing to provide quick determinations.