Systems and methods for implementing a machine learning approach to modeling entity behavior
US10754946B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 5, 2018 |
| Grant date | Aug 25, 2020 |
| Priority date | — |
| Expiry date | Feb 14, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods are provided for implementing a machine learning approach to modeling entity behavior. Fixed information and periodically updated information may be utilized to predict the behavior of an entity. By incorporating periodically updated information, the system is able to maintain an up-to-date prediction of each entity's behavior, while also accounting for entity action with respect to ongoing obligations. The system may generate behavior scores for the set of entities. In some embodiments, the behavior scores that are generated may indicate the transactional risk associated with each entity. Using the behavior scores generated, a user may be able to assess the credit riskiness of individual entities and instruct one or more individuals assigned to the entities to take one or more actions based on the credit riskiness of the individual entities.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.