Capital One Services, LLC

Ryan M Parker

Chris Demchalk

Lokesh Vijay Kumar

Brian Fromknecht

Poornima Bagare Raju

Jeffrey Allan Thompson

Lin Ni Lisa Cheng

Satish Chikkaveerappa

Nishant Kumar Sinha

Ponnazhakan Subramanian

Sasi Kumar Unnikrishnan

Paul Cho

Venkata Satya Parcha

Sravankumar Karanam

Lavika Aggarwal

Rhic Chowdhury

Nimish Mangal

Jacob Adair

Gary B Williams

Piper Alexandra Coble

Matthew Kevin Sullivan

Natalie Kuhn

Sergey Petrunin

Eric Campbell

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

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

A system, processes, and a computer-readable storage medium are provided method includes receiving a search query including one or more of a textual phrase, a document, or data including metadata from a user. For example, a processor may execute a theme-generating machine learning algorithm to generate a theme of the search query. Profiles of other users are identified as similar to a profile of the user may be located. A search history of each of the located other users may be located in the collected search history. Content in the searchable content that corresponds to the generated theme of the search query and according to a result of the evaluation of the located search history of each of the other users may be obtained. The obtained content may be scored based on a scoring algorithm and output a set of scored search results to the input/output device.

Techniques and systems for smart natural language processing of search results

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

Described herein is a system for executing a computing module. Described herein is a system for executing a computing module. The system may determine whether a function of a computing module is suitable to be executed using multi-coring. The system identifies one or more available computing cores and executes the function on the one or more available computing cores. The one or more available computing cores can be dedicated to execute the function until the execution of the function is complete. The one or more available computing cores execute the tasks of the function asynchronously. The system receives output data from the function asynchronously in a list data structure. The system can maintain a desired order of the output data in the list data structure.

Executing computing modules using multi-coring

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Dallas, TX, United States of America

Ryan M Parker