Systems and methods for using machine learning techniques to predict institutional risks
US11645712B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 16, 2021 |
| Grant date | May 9, 2023 |
| Priority date | — |
| Expiry date | Apr 16, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q10/0635
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for entity risk management are disclosed. A system for entity risk management may include a memory storing instructions and at least one processor configured to execute instructions to perform operations including: establishing a connection between the system and a data source, the data source being remote from the system and associated with a first entity; receiving first document data from the data source; normalizing the first document data; classifying the normalized document data; extracting model input data from the classified document data; applying a machine learning model trained to predict risk levels using second document data to the extracted model input data to predict a risk level associated with the first entity; generating analysis data based on the predicted risk level; and based on the analysis data, transmitting an alert to a management device communicably connected to the system.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.