Capital One Financial had 40 patents in big data during Q4 2023. The patents filed by Capital One Financial Corp in Q4 2023 focus on improving data processing efficiency for classifying user files with a temporal element, organizing and monitoring content delivery networks, enhancing vehicle identification with preprocessing, improving data processing systems by generating staging data independently from control scripts, and provisioning account information securely for payment cards. These methods and systems aim to enhance efficiency, speed, and quality in various data processing and management tasks. GlobalData’s report on Capital One Financial gives a 360-degreee view of the company including its patenting strategy. Buy the report here.

Capital One Financial grant share with big data as a theme is 50% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.

Recent Patents

Application: Methods and systems for classifying database records by introducing time dependency into time-homogeneous probability models (Patent ID: US20230418843A1)

The patent filed by Capital One Financial Corp. describes methods and systems for enhancing the efficiency of classifying user files in a database by incorporating time dependency into time-homogeneous probability models. By introducing time dependency into these models, the system aims to improve the accuracy and effectiveness of classifying user files with a temporal element. The system includes cloud-based storage and control circuitry to store user records, retrieve user record history, and determine probabilities of user records belonging to different states based on historical data. Additionally, the system generates recommendations for users based on the output of the probability models.

The method outlined in the patent involves receiving requests to determine probabilities of user records belonging to various states, retrieving user record history, and selecting stochastic probability models based on the number of periodic status checks in the history. By utilizing different stochastic probability models for different ranges of status checks, the system can provide more accurate classifications and recommendations. The method also includes processing feature inputs, generating probability distribution vectors, and forecasting status changes related to user records. Overall, the patent focuses on leveraging time dependency in probability models to enhance the efficiency and accuracy of classifying user files in a database, particularly those with a temporal element.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.