Systems and methods for predictive analysis of electronic transaction representment data using machine learning
US12314960B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 7, 2022 |
| Grant date | May 27, 2025 |
| Priority date | — |
| Expiry date | Dec 22, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are disclosed for generating a prediction on chargeback representment based on probability data and/or results from a plurality of machine learning models. The method includes receiving data associated with at least one disputed transaction for at least one user, wherein the received data includes user-specific information and/or merchant-specific information. The received data is processed to calculate a probability of success in a chargeback representment for the at least one disputed transaction. A prediction is calculated based, at least in part, on the probability of success, one or more results from a plurality of machine learning models, or a combination thereof. A presentation is generated of at least one recommendation on the chargeback representment based, at least in part, on the prediction in a user interface of at least one device associated with the at least one user.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.