Deep learning for credit controls
US11625569B2 · kind B2 · utility
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7References
26Claims
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Key dates
| Filing date | Mar 23, 2017 |
| Grant date | Apr 11, 2023 |
| Priority date | — |
| Expiry date | Mar 30, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q40/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are provided to identify abnormal transaction activity by a participant that is inconsistent with current conditions. Historical participant and external data is identified. A recurrent neural network identifies patterns in the historical participant and external data. A new transaction by the participant is received. The new transaction is compared using the patterns to the historical participant and external data. An abnormality score is generated. An alert is generated if the abnormality score exceeds a threshold.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.