1. A computer-implemented method for generating fraud indication within a prospective payment system (PPS), the method being implemented by one or more data processors forming part of at least one computer and comprising: generating, by at least one data processor, profiles of service provider activities rendered for payment by a facility, the profiles being dynamically derived from transactional level data associated with service provider activities; calculating, by at least one data processor, summary variables from the profiles input into an unsupervised predictive model for at least one particular metric, the at least one metric at any desired level of and associated with the PPS comprising one of: an indicator of total costs claimed by the facility at that level; an indicator of the facility's average patient length of stay at that level; and an indicator of total claims made by the facility at that level; determining, by at least one data processor, a deviation measure based on comparing the summary variables with industry-wide peer data for the particular metric, wherein comparing the summary variable with industry-wide peer data comprises: determining, by at least one data processor, a first distribution based on the summary variables; determining, by at least one data processor, a second distribution based on the industry-wide peer data; and detecting, by at least one data processor, aberrations between the first distribution and the second distribution; integrating, by at least one data processor, the aberrations detected to produce normalized variables; and deriving, by at least one data processor, an indicator from the deviation measure, the indicator representing the fraud indication based on aberrations associated with the deviation measure; wherein a profile is generated by: generating a profile of a first entity, generating a profile of at least one second entity that interacts with the first entity through transactions with the first entity, generating a profile of at least one third entity comprising a combination of the profiles of the interacting first and second entities, and enhancing the profile of the first entity with the profile of the at least one third entity, wherein an interacting pair of entities is itself an entity.
1. A computer-implemented method for generating fraud indication within a prospective payment system (PPS), the method being implemented by one or more data processors forming part of at least one computer and comprising: generating, by at least one data processor, profiles of service provider activities rendered for payment by a facility, the profiles being dynamically derived from transactional level data associated with service provider activities; calculating, by at least one data processor, summary variables from the profiles input into an unsupervised predictive model for at least one particular metric, the at least one metric at any desired level of and associated with the PPS comprising one of: an indicator of total costs claimed by the facility at that level; an indicator of the facility's average patient length of stay at that level; and an indicator of total claims made by the facility at that level; determining, by at least one data processor, a deviation measure based on comparing the summary variables with industry-wide peer data for the particular metric, wherein comparing the summary variable with industry-wide peer data comprises: determining, by at least one data processor, a first distribution based on the summary variables; determining, by at least one data processor, a second distribution based on the industry-wide peer data; and detecting, by at least one data processor, aberrations between the first distribution and the second distribution; integrating, by at least one data processor, the aberrations detected to produce normalized variables; and deriving, by at least one data processor, an indicator from the deviation measure, the indicator representing the fraud indication based on aberrations associated with the deviation measure; wherein a profile is generated by: generating a profile of a first entity, generating a profile of at least one second entity that interacts with the first entity through transactions with the first entity, generating a profile of at least one third entity comprising a combination of the profiles of the interacting first and second entities, and enhancing the profile of the first entity with the profile of the at least one third entity, wherein an interacting pair of entities is itself an entity. 4. The computer-implemented method according to claim 1 , wherein the transaction level data is obtained from updates made to transactional level data associated with the facility.