INTERLEAVED SEQUENCE RECURRENT NEURAL NETWORKS FOR FRAUD DETECTION

• Main Authors: BRANCO, Bermardo Jose Numes De, Almeida, ALMEIDA, Mariana, S.C, ASCENSAO, Joao Tiago Barriga, Negra, GOMES, Ana Sofia, Leal, ABREU, Pedro, Caldeira, BIZARRO, Bernardo Gustavo Santos, Rodrigues
• Format: Patent
• Language: English; French; German
• Published: 09.08.2023
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

A process for handling interleaved sequences using RNNs includes receiving data of a first transaction, retrieving a first state (e.g., a default or a saved RNN state for an entity associated with the first transaction), and determining a new second state and a prediction result using the first state and an input data based on the first transaction. The process includes updating the saved RNN state for the entity to be the second state. The process includes receiving data of a second transaction, where the second transaction is associated with the same entity as the first transaction. The process unloops an RNN associated with the saved RNN state including by: retrieving the second state, determining a new third state and a prediction result using the second state and an input data based the second transaction, and updating the saved RNN state for the entity to be the third state.