Abstract: Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Various embodiments also include automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy, automatically recommending, based on the assessed risk, computer network changes to reduce the assessed risk, and providing one or more recommended computer network changes to reduce the assessed risk. Various embodiments further include enactment by the entity of at least one of the one or more of the recommended computer network changes to reduce the assessed risk to the entity, determining that the entity has enacted at least a portion of the recommended computer network changes, and in response, automatically reassessing the risk of a cyber security failure based on the enacted recommended computer network changes.

Abstract: Various embodiments of the present technology relate to diversity and similarity analysis. In some exemplary embodiments, a method includes, for each of a plurality of entities, receiving a set of variables that are indicative of attributes of an entity. The exemplary method also includes comparing the sets of variables for the plurality of entities to each other, locating clusters of similar variables shared between two or more of the plurality of entities, determining a probable maximum loss for the plurality of entities that share the clusters, the probable maximum loss being a loss value attributed to a cyber event against one or more of the shared variables, receiving feedback from an end user in response to providing the probable maximum loss to the end user, and updating the probable maximum loss in response to the feedback.

Abstract: Various embodiments of the present technology relate to diversity and similarity analysis. In some exemplary embodiments, a method includes, for each of a plurality of entities, receiving a set of variables that are indicative of attributes of an entity. The exemplary method also includes comparing the sets of variables for the plurality of entities to each other, locating clusters of similar variables shared between two or more of the plurality of entities, determining a probable maximum loss for the plurality of entities that share the clusters, the probable maximum loss being a loss value attributed to a cyber event against one or more of the shared variables, receiving feedback from an end user in response to providing the probable maximum loss to the end user, and updating the probable maximum loss in response to the feedback.