Credit card transaction risk prediction method based on federated learning

• Main Authors: LI LI, FAN YUXI, LIN GUOYI
• Format: Patent
• Language: Chinese; English
• Published: 26.02.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention relates to a federated learning-based credit card transaction risk prediction method, and the method comprises the following steps: 1) obtaining a data set about client credit card transaction feature data in each bank serving as different local clients; 2) searching similar instances in each bank data set by adopting a locality sensitive hash algorithm; 3) constructing combined features by adopting a GBDT algorithm in a serial federated learning environment; 4) constructing a new training feature according to the combined feature and the original feature, and expanding and constructing a new data set by each local client; 5) enabling each local client to adopt the same neural network model for training, uploading the trained model parameters to the cloud, and enabling the cloud to aggregate and update the model parameters and returns the model parameters to each local client to start the next training until the training process converges, so that the final neural networkmodel is obtained to com