Automated risk prioritization and default detection

US12020319B2 · kind B2 · utility

Assignee

• CAPITAL ONE SERVICES, LLC · US

Inventors

• Pedro Partiti De Oliveira · Dallas, US
• Marrian Kitchens · Delba, US
• Papa D. Ndiaye · Kenner, US
• Joseph T. Allison · Prosper, US
• Collin Longmire · McKinney, US
• John Runge · Plano, US
• Dong Ji · Plano, US
• Abhishek TEWARI · Prayagraj, IN
• Bing Liu · Brookline, US

Key dates

• Filing date: Jun 27, 2022
• Grant date: Jun 25, 2024
• Expiry date: Jun 27, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06Q40/03
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

Systems, methods, and apparatuses for automatically detecting the risk of dealer default are described. A machine learning model may be trained using a gradient boosting technique on a dataset that includes historical lien information, historical dealer information, and historical vehicle default information. Lien information and financing information for vehicles may be received and correlated. Furthermore, a machine learning model may generate aggregate risk scores for dealers. Furthermore, determination of an aggregate risk score that exceeds a threshold risk score may cause the generation of a notification.