OCR Date Alignment for Bank Statement Identification
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Solution Overview
Problem
Existing document processing systems struggle to accurately identify bank statements due to their varied sizes and shapes, leading to inefficiencies in loan application processes when statements are missing or incorrectly identified.
Innovation Solution
A system utilizing optical character recognition to process document image data, identify dates, and analyze their alignment and temporal proximity to determine if a document is a statement, with user verification through graphical user interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional document processing methods are used to identify bank statements, then the system can process documents, but the accuracy of identification deteriorates due to varied document sizes and shapes
Solution Approach 1:
The patent extracts the date field as a distinctive feature from the document image, using optical character recognition to identify and locate dates. By focusing on this specific characteristic rather than analyzing the entire document structure, the system achieves accurate identification despite variations in document size and shape.
Solution Approach 2:
The system applies local quality analysis by examining specific regions of the document where dates are typically located. It uses position data to determine if dates are aligned in a first direction (such as vertically or horizontally), which is a local structural characteristic that remains consistent across different bank statement formats.
2Productivity
If automated document recognition systems are used, then processing speed increases, but the reliability of statement identification deteriorates due to lack of understanding document characteristics
Solution Approach 1:
The system performs preliminary actions by automatically extracting date information and position data before making the identification decision. It pre-processes the document image to create language data and position data, then uses this prepared information to quickly and reliably determine whether the document is a bank statement.
Solution Approach 2:
The patent replaces traditional mechanical document review methods with automated optical character recognition and computational analysis. The system uses algorithms to analyze date patterns, alignment, and temporal proximity, substituting human judgment with automated processing that maintains both speed and reliability.
3Measurement precision
If the system analyzes multiple document characteristics, then identification accuracy improves, but the computing power requirements increase
Solution Approach 1:
The system extracts only the most relevant characteristic (date information) from the document image for analysis. By focusing on dates and their positional relationships rather than analyzing all visual features, the system achieves high identification accuracy with minimal computing resources.
Solution Approach 2:
The patent applies partial action by analyzing only the specific feature (dates) that is sufficient for reliable identification. It does not attempt to analyze every aspect of the document, but rather focuses on the partial feature set that provides the necessary information for accurate statement detection.
4Measurement precision
If the system processes all documents manually, then verification accuracy is high, but the time required for processing increases
Solution Approach 1:
The system performs self-service by automatically extracting and analyzing date information from document images. It independently completes the identification task through automated optical character recognition and computational analysis, eliminating the need for manual review while maintaining accuracy.
Solution Approach 2:
The system incorporates feedback mechanisms where it presents its identification results to users for verification. The user interface allows users to review the system's analysis and provide feedback, which can be used to refine future automated processing while maintaining both speed and accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the accuracy and speed of identifying bank statements by focusing on common date patterns, reducing computing power requirements, and allowing user interaction for verification, thus improving the loan application process.
Implementation Method 1
process, using optical character recognition, the document image data to create language data and position data associated with the language data
Data Source
AI summary
Disclosed embodiments may include a system for identifying a statement. This may include receiving document image data which is then processed using optical character recognition to create language data and position data. The system may include identifying a plurality of dates from the language data and determining whether the plurality of dates is aligned in a first direction using the position data. The system may include determining whether the plurality of dates is within a predetermined time threshold or counting the plurality of dates to determine whether the count is greater than a predetermined count threshold. The system may create a label for the document and generate and transmit a graphical user interface to a user device for displaying the label and/or the document image data. The user may be able to interact with the user device to change the document label.