Document Data Verification System for Title Examination
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Solution Overview
Problem
The process of determining the quality of title policies for real property transfers is laborious due to the lack of electronic searching systems in many jurisdictions, requiring title examiners to manually inspect and verify each document in the property's chain of title, which is time-consuming and inefficient.
Innovation Solution
A data verification system that presents document images to operators, allowing them to input and verify machine-recognized data elements, with features like color-coding based on match measures and selective prompting for re-input, to enhance the accuracy and efficiency of data extraction and validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection of each document in the chain of title is performed, then accuracy of title examination is maintained, but time consumption and labor intensity increase significantly
Solution Approach 1:
The patent segments the title examination process into distinct phases: machine recognition of data elements from document images, validation against business rules, and selective human verification. This segmentation allows automated processing of routine tasks while reserving human expertise for complex judgment calls, thereby reducing time consumption without sacrificing accuracy.
Solution Approach 2:
The patent introduces an intermediary validation system that acts as a bridge between machine recognition and human examination. This intermediary layer performs automated validation of recognized data elements against business rules, filtering out obvious errors before human review and reducing the burden on examiners while maintaining overall accuracy.
2Productivity
If electronic searching systems are implemented, then search efficiency improves, but system complexity and initial cost increase
Solution Approach 1:
The patent creates a multi-functional system that performs multiple tasks: optical character recognition of document images, extraction of data elements, validation against business rules, and integration with existing electronic index systems. This universal system consolidates multiple functions into a unified platform, improving search efficiency while managing complexity through integration rather than proliferation of separate systems.
Solution Approach 2:
The system incorporates self-service capabilities through automated validation of recognized data elements against stored business rules. The system automatically identifies and flags potential errors without requiring constant human intervention, reducing operational complexity while maintaining high productivity.
3Productivity
If machine recognition is used to extract data elements, then processing speed increases, but accuracy and reliability of extracted data decrease
Solution Approach 1:
The patent implements feedback mechanisms where recognized data elements are validated against stored business rules, and results are used to adjust and improve the recognition process. Error feedback from validation failures is used to refine recognition algorithms, creating a continuous improvement cycle that maintains high processing speed while progressively improving accuracy and reliability.
Solution Approach 2:
The system performs preliminary validation of machine-recognized data elements against business rules before final acceptance. This preliminary action catches obvious errors early in the process, allowing for correction before the data is finalized, thereby maintaining processing speed while improving the reliability of extracted data.
Data Source
AI summary
A data verification system is configured to verify machine-recognized data elements acquired during a machine-implemented data acquisition process. The system includes a data verification workstation, a image server, and a data entry server. The data verification workstation is configured to obtain document images from the image server, present portions of document images to an operator, wherein the document images include text, and receive input from the operator based on the text. The input includes data elements. The data verification workstation is also configured to acquire machine-recognized data elements from the data entry server. The machine-recognized data elements were acquired from the document image during a machine-implemented data acquisition process based on the text. The data verification workstation is also configured to compare the data elements received from the operator to the machine-recognized data elements and selectively prompt the operator to re-input the data elements based on the comparison.