Training and selection of multiple fraud detection models
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United States of America Patent
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May 25, 2017
app pub date -
Nov 24, 2015
filing date -
Nov 24, 2015
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Abstract
A payment processing system continuously processes transactions. Multiple modeling technologies are used within a fraud detection system to each handle different blocks of segmented transaction data in order to detect fraud. Model data is created from recent segmented transaction data that is currently handled by an existing model; each transaction includes a fraud flag as to whether it was fraudulent or not. The model data is used to train, validate and test any of a number of types of models where the fraud flag is the target. Performance metrics such as Sensitivity, Review Rate and False Positives are calculated for each trained model. An operational objective is used to determine a value for a particular performance metric which then dictates values for other performance metrics for each model. The best model is chosen by optimizing the performance metrics. The best model is configured and deployed to replace the existing model.
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