Most claim payers identify potential subrogation cases internally using industry experience and plan members’ responses to questionnaires. This traditional method of investigation is not wholly reliable or as inexpensive as perceived, since it relies on plan member cooperation and truthfulness that requires further follow up. Moreover, some claims with recovery potential can be missed.
Data Mining methodically explores claim data with a series of investigative techniques. It finds more cases that represent substantial financial opportunity for claim payers, but is more expensive due to technical processes and claim data interchanges.
SRP best of both approach
SRP offers a pragmatic approach for claim payers to maximize recovery opportunities and control identification costs by combining traditional investigation with data mining. We encourage clients to identity all subrogation cases they can internally, which typically represents most opportunities. For such cases, our subrogation charges are half of the contingent fee for data mined cases. Then, use SRP Data Mining only to identify cases that are missed. Our best of both approach ensures maximum case identification and recoveries at low costs that clients can control.
SRP Data Mining provides clients with the key advantage of data matching with existing, third-party claim information, which removes the uncertainties of plan members’ responsiveness, truthfulness and recall accuracy. Whether used for 100% of case identification, or as a “second pass” to find cases that are missed using traditional methods, our data mining services ensure peace of mind for claim payers, knowing that every potential recovery opportunity is captured.
