An outlier detector that exploits the existing risk structure of the decision problem in order to discover risk assignments that are globally inconsistent is described. The technique works on a set of candidates for which risk categories have already been assigned. In the case of insurance underwriting, the invention pertains to the premium class assigned to an application. For this set of labeled candidates, the system finds all such pairs of applications belonging to different risk categories, which violate the principle of dominance. The invention matches the risk ordering of the applications with the ordering imposed by dominance and uses any mismatch during the process to identify applications that were potentially assigned incorrect risk categories.