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