Financial Record Image Error Detection via OCR Data Lift
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Solution Overview
Problem
Organizing and analyzing large volumes of image records, particularly financial transaction images, is challenging due to varied storage periods, diverse types of records, and the difficulty in determining which images need processing and retention.
Innovation Solution
A system utilizing a computer apparatus with a processor and memory, equipped with a software module that applies optical character recognition (OCR) to extract data from images, identifies errors, and determines authorization for processing financial records by comparing payee and user names, and sends images to an investigation group as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual organization and analysis of image records is performed, then accuracy in determining which images need processing can be maintained, but productivity decreases due to large volume and variety of records
Solution Approach 1:
The patent replaces manual mechanical review of images with an automated computer-based system that uses optical character recognition (OCR) to extract and analyze data from images. The system automatically determines which images require processing by comparing extracted data against retention criteria, eliminating the need for manual organization and analysis while maintaining accuracy through systematic data extraction and comparison algorithms.
2Reliability
If all image records are retained for extended periods, then reliability of financial record keeping is improved, but loss of storage space increases
Solution Approach 1:
The patent extracts only the essential data elements from images using OCR technology, such as check amounts, dates, and account numbers. This extracted data is then stored in a compact digital format rather than retaining all original image files. The system retains only the extracted data and essential image references, significantly reducing storage requirements while maintaining the reliability needed for financial record-keeping through structured data extraction and selective retention.
3Adaptability or versatility
If multiple types of financial records are processed through a single system, then adaptability of the system is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal processing system that handles multiple types of financial records including checks, deposit slips, and payment advices through a single integrated platform. The system uses a common OCR-based data extraction mechanism that automatically adapts to different record types by identifying and extracting relevant data elements specific to each type, eliminating the need for separate processing systems while managing complexity through standardized extraction and retention criteria application.
Data Source
AI summary
Embodiments for identifying errors based on data extracted from financial record images includes systems that receive one or more financial record images from a user, apply an optical character recognition process to at least a portion of the one or more financial record images, and identify record data based on the applied optical character recognition process comprising at least a name of a party to the financial record. The systems further identify errors associated with the one or more financial record images based on the record data.