Abstract: Data is received that includes a data set characterizing a plurality of insurance provider profiles and/or claims. Thereafter, a minimum volume ellipsoid is determined for the data set. Subsequently, at least one provider profile and/or claim is identified having at least one outlier variable based on a distance that the at least one provider profile and/or claim has relative to a center point of the minimum volume ellipsoid. Data is then provided (e.g., displayed, stored, loaded into memory, transmitted to a remote computing system, etc.) that characterizes the at least one provider profile and/or claim as likely being fraudulent or erroneous. In other variations, the minimum volume ellipsoid is determined using a different data set. Related apparatus, systems, techniques and articles are also described.

Abstract: Data is received that comprises a data set characterizing a plurality of insurance claims. Thereafter, a density function of the data set is estimated using kernel density estimation. At least one claim having at least one outlier variable is then identified using the density function. Data is then provided (e.g., displayed, stored, loaded into memory, transmitted to a remote computing system, etc.) that characterizes the at least one identified claim as likely being fraudulent or erroneous. Related apparatus, systems, techniques and articles are also described.