International Business Machines Corporation
FRAUD DETECTION USING MULTI-TASK LEARNING AND/OR DEEP LEARNING
Last updated:
Abstract:
Application of multi-task learning technique(s) to machine logic (for example, software) used to detect financial transactions that are fraudulent or at least considered likely to be fraudulent. Some embodiments include adjustments and/or additions to conventional multi-task learning techniques in order to make the multi-task learning techniques more suitable for use in fraud detection software. One example of this is compensation for class imbalances that are to be expected as between the likely-fraud and not-likely-fraud classes of data sets (for example, training data sets, runtime data sets).
Status:
Application
Type:
Utility
Filling date:
8 Jul 2020
Issue date:
13 Jan 2022