Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for fraudulent scheme detection. In one embodiment, a time-evolving graph-based solution is presented for the Ponzi scheme detection. For the solution, unbounded and time-based relational data is transformed to the time-evolving graph structure. Time-based aggregate metrics are computed and captured based in part on changes occurring within user accounts and transactions identified within the time-evolving graph structure. Then, with the aid of know pattern flows and the application of filtering rules, detection of such a fraudulent scheme may be accomplished.

Abstract: A method is provided that includes assigning one or more first records of a first table and one or more second records of a second table to corresponding range groups of a plurality of range groups. The method further includes comparing at least one record of the first table with at least one record of the second table, where the at least one record of the first table and the at least one record of the second table are assigned to a first range group of the plurality of range groups. The method also includes, based on the comparing, identifying a parent record and a child record and segmenting the parent record based on the child record. Further, the method includes subsequent to the segmenting the parent record, performing a join operation on the first table and the second table.