Source Document Data Entry Automation via OCR
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Solution Overview
Problem
Current methods for data entry from source documents, such as tax-related forms, are time-consuming and require manual input, lacking efficient automation for data extraction and association with specific fields, leading to potential errors and inefficiencies in data processing for professional service providers.
Innovation Solution
A system and method for Source Document Data Entry (SDDE) that utilizes OCR capabilities to extract and associate data from source documents with specific fields, allowing for automated data processing and verification, integrated with tools like Thomson Reuters' FileCabinet CS and UltraTax CS, enabling efficient data management and organization within e-folders for secure sharing and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data entry is used to input data from source documents into forms, then data accuracy can be verified through peer review, but the process is time-consuming and tedious
Solution Approach 1:
The patent replaces the mechanical manual data entry process with an automated optical character recognition (OCR) system. The OCR software automatically extracts data from source documents and populates form fields, eliminating the need for manual typing while maintaining data accuracy through automated verification processes.
Solution Approach 2:
The system enables self-service by allowing the OCR software to automatically extract and transfer data without requiring manual intervention. The automated data extraction process serves itself by identifying and populating relevant information from source documents into the appropriate form fields.
2Extent of automation
If OCR techniques are used to extract data from source documents, then data extraction is automated, but the extracted data needs to be associated with particular entities and fields
Solution Approach 1:
The patent introduces an intermediary layer between OCR data extraction and form population. This intermediary system matches extracted data with form fields using pattern recognition and data type analysis, automatically associating extracted information with the appropriate entities and fields without requiring manual configuration.
Solution Approach 2:
The system changes parameters by analyzing the structure and content of extracted data to determine its appropriate destination. By examining data characteristics such as format, type, and context, the system dynamically routes extracted information to the correct form fields and entities.
3Ease of operation
If data is independently input into separate forms, then each form can be completed individually, but data collected from one form cannot be efficiently used in other forms
Solution Approach 1:
The patent creates a universal data extraction system that can populate multiple different form types from a single source document. The OCR system extracts data once and makes it available for use across various form formats and entities, eliminating redundant data entry while maintaining the ability to complete different forms independently.
Data Source
AI summary
The present invention provides software and a method and system of efficient source document data entry and data association. More particularly, the present invention relates to a software module which receives source documents and recognizes or extracts information from the documents or associated files for use in populating fields of related or derivative documents or screens to facilitate accurate transfer of data. The invention also allows for ease in confirming the accuracy of the extracted or imported data by comparison with the source document either directly by a person or through automated or semi-automated procedures.