Rule based machine learning for precise fraud detection
US12112331B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 1, 2021 |
| Grant date | Oct 8, 2024 |
| Priority date | — |
| Expiry date | Nov 25, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems for rule-based machine learning for precise fraud detection. One system includes an electronic processor configured to determine, via a decision tree, a first subset of datasets of an aggregate dataset collection generated using a rule-based model. The electronic processor is also configured to select a third collection of datasets, each dataset included in the third collection of datasets associated with a user characteristic associated with fraud. The electronic processor is also configured to determine, via the decision tree, a second subset of datasets of the third collection of datasets, each dataset included in the second subset of datasets associated with a second set of user characteristics associated with fraud. The electronic processor is also configured to, in response to determining that an accuracy score associated with the second set of user characteristics satisfies a threshold, generate and transmit a report for display.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.