Machine learning optimization for fraud detection
US11276023B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 6, 2019 |
| Grant date | Mar 15, 2022 |
| Priority date | — |
| Expiry date | Mar 6, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q20/4016
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Devices and techniques are generally described for fraud detection. A machine learning model is used to determine a first fraud risk score for a first transaction. The machine learning model includes a first set of weights. A first covariance matrix is determined for the machine learning model based at least in part on the first fraud risk score. A second set of weights for the machine learning model is determined. The second set of weights is determined based on the first set of weights and the first covariance matrix. In various examples, the machine learning model with the second set of weights is used to determine a second fraud risk score for a second transaction. A fraud decision surface is determined and the second fraud risk score is compared to the fraud decision surface. Data indicating that the second transaction is fraudulent is sent to a computing device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.