Capital One Services, LLC

Lokesh Vijay Kumar

Chris Demchalk

Ryan M Parker

Poornima Bagare Raju

Brian Fromknecht

Satish Chikkaveerappa

Ponnazhakan Subramanian

Sasi Kumar Unnikrishnan

Venkata Satya Parcha

Nishant Kumar Sinha

Nimish Mangal

Jacob Adair

Rhic Chowdhury

Lavika Aggarwal

Renjith Pascas

Disclosed herein are system, method, and computer program product embodiments for rapid identification and access to relevant regulatory documents. A data model relating regulatory mandates and requirements to citations appearing within an enforcement document is used to rapidly access specific citations within an enforcement document. In the case of image-based enforcement documents, the originality of these documents is preserved while allowing a user to see where the relevant citations appear in the document images. The relevant citations are further compared to business policies to identify potential impacts of regulatory mandates and requirements.

Citation and policy based document classification

In some implementations, a browser plugin may receive, from a web browser executed by a user device, an indication of a vehicle make and a vehicle model. The browser plugin may transmit, to an API function associated with the vehicle database, a query indicating the vehicle make and the vehicle model. The browser plugin may receive, from the vehicle database, a response indicating at least a quantity of matching vehicles. The browser plugin may output instructions for a pop-up window in the web browser that indicates the quantity of matching vehicles and that includes an element linking to the website associated with the vehicle database.

Web browser plugin redirecting to a website for a vehicle database

Provided herein are systems and methods for extracting text from a document. Different optical character recognition (OCR) tools are used to extract different versions of the text in the document. Metrics evaluating the quality of the extracted text are compared to identify and select higher quality extracted text. A selected portion of text is compared to a threshold to ensure minimal quality. The selected portion of text is then saved. Error correction can be applied to the selected portion of text based on errors specific to the OCR tools or the document contents.

Text extraction using optical character recognition

Disclosed herein are system, method, and computer program product embodiments for rapid identification and access to relevant regulatory documents. A data model relating regulatory mandates and requirements to citations appearing within an enforcement document is used to rapidly access specific citations within an enforcement document. In the case of image-based enforcement documents, the originality of these documents is preserved while allowing a user to see where the relevant citations appear in the document images.

Section-linked document classifiers

Disclosed herein are system, method, and computer program product embodiments for categorizing customer complaints on social media using a model trained on customer voice calls or chats with agents. Additionally, users interested in monitoring regulatory compliance issues based on customer complaints can receive notifications regarding complaints that are linked to regulatory topic areas, without the need to manually scan vast numbers of social media postings.

Cognitive analysis of public communications

Disclosed herein are system, method, and computer program product embodiments for identifying and managing emerging risks. Businesses, such as those participating in regulated industries, may need to regularly monitor enforcement actions that are cited in a variety of sources. Embodiments disclosed herein provide for scraping information from those sources and comparing it to existing risk events in order to determine possible discrepancies that should be assessed.

Compliance management for emerging risks

A device receives vehicle data associated with vehicles located at a vehicle dealership lot, and receives, from a user device, profile data identifying a user of the user device and data identifying a particular vehicle of the vehicles. The device compares the data identifying the particular vehicle and the vehicle data to determine particular vehicle data associated with the particular vehicle, and processes the particular vehicle data and the profile data of the user, with a first model, to determine purchase options for the particular vehicle and the user. The device provides, to the user device, the particular vehicle data and the purchase options for the particular vehicle to cause the user device to display the particular vehicle data and the purchase options for the particular vehicle.

Utilizing machine learning to generate vehicle information for a vehicle captured by a user device in a vehicle lot

Methods and systems for updating configurations. An application can be determined to be incorrectly configured. A request can be sent to update a configuration property. The configuration property can be updated in a test environment. The application can be tested with the updated configuration property in the test environment. The test of the application with the updated configuration property in the test environment can be identified as successful. An incorrect configuration of the application can be updated.

Methods and systems for managing application configurations

A device may receive third-party data associated with merchants and may receive customer interest data associated with customers of the merchants, wherein the customer interest data includes data identifying locations of the customers and birthdates of the customers. The device may train a machine learning model, with the third-party data and the customer interest data, to generate a trained machine learning model. The device may receive, from a user device, data identifying a location and a birthdate of a particular customer of a particular merchant, wherein the particular merchant is one of the merchants, and may process the data identifying the location and the birthdate of the particular customer, with the trained machine learning model, to determine a predicted interest of the particular customer. The device may perform one or more actions based on the interest of the particular customer.

Method, device, and non-transitory computer readable medium for utilizing a machine learning model to determine interests and recommendations for a customer of a merchant

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Frisco, TX, United States of America

Lokesh Vijay Kumar