Artificial intelligence based fraud detection system
US11580339B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 13, 2019 |
| Grant date | Feb 14, 2023 |
| Priority date | — |
| Expiry date | Jul 25, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments detect fraud of risk targets that include both customer accounts and cashiers. Embodiments receive historical point of sale (“POS”) data and divide the POS data into store groupings. Embodiments create a first aggregation of the POS data corresponding to the customer accounts and a second aggregation of the POS data corresponding to the cashiers. Embodiments calculate first features corresponding to the customer accounts and second features corresponding to the cashiers. Embodiments filter the risk targets based on rules and separate the filtered risk targets into a plurality of data ranges. For each combination of store groupings and data ranges, embodiments train an unsupervised machine learning model. Embodiments then apply the unsupervised machine learning models after the training to generate first anomaly scores for each of the customer accounts and cashiers.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.