18060149. ELECTRONIC DOCUMENT VALIDATION simplified abstract (Capital One Services, LLC)

ELECTRONIC DOCUMENT VALIDATION

Organization Name

Capital One Services, LLC

Inventor(s)

Sunilkumar Krishnamoorthy of Glen Allen VA (US)

ELECTRONIC DOCUMENT VALIDATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18060149 titled 'ELECTRONIC DOCUMENT VALIDATION

Simplified Explanation

The abstract describes a patent application for a device that can analyze an electronic document to determine its type and compare it to an expected document.

• Device extracts a portion of an electronic document.
• Obtains first text data associated with the portion.
• Determines if the first text data matches any text indicators of document types.
• If not, obtains second text data from a larger portion of the document.
• Uses a machine learning model to determine the type of the document based on the second text data.
• Compares the type of the document to an expected document.
• Sends a notification if the document is not the expected one.

Potential Applications

This technology could be applied in various industries such as legal, financial, and healthcare sectors for document verification and fraud detection.

Problems Solved

This technology helps in automating the process of document analysis and verification, saving time and reducing human error.

Benefits

The device provides a quick and accurate way to determine the type of electronic documents, ensuring data integrity and security.

Potential Commercial Applications

"Document Type Verification Device: Enhancing Document Security and Integrity"

Possible Prior Art

One possible prior art could be software applications that analyze text data for document classification and verification purposes.

How does the machine learning model determine the type of the electronic document?

The machine learning model likely uses patterns and features in the text data to classify the document into different types.

What criteria are used to determine if the document type differs from the expected document?

The criteria could include specific keywords, formatting, or content structure that are expected in the document type.

Original Abstract Submitted

In some implementations, a device may obtain an electronic document. The device may extract a portion of the electronic document. The device may obtain first text data associated with the portion. The device may determine whether the first text data corresponds to any of a plurality of text indicators of document types. The device may obtain, based on a determination that the first text data does not correspond to any of the plurality of text indicators, second text data associated with a greater portion of the electronic document that includes more than the first text data. The device may determine, using a machine learning model, a type of the electronic document based on the second text data. The device may determine whether the type of the electronic document differs from an expected document. The device may transmit a notification indicating that the electronic document is not the expected document.