AI Data Verification System with Dynamic Method Segmentation
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Solution Overview
Problem
Companies face challenges in verifying and updating customer and business data accurately and efficiently, particularly due to resource constraints and the need for real-time data integrity, which existing methods fail to address effectively.
Innovation Solution
A data verification system utilizing artificial intelligence to select and dynamically adjust verification methods such as web-crawling, tele-verification, agent web verification, direct-mail, and email verification, segmenting data based on characteristics, and applying lower-cost methods for larger datasets and higher-cost methods for subsets, ensuring data accuracy and cost-effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple verification methods are applied to all data records, then data verification accuracy is improved, but verification cost increases
Solution Approach 1:
The patent segments the data verification process into multiple stages, applying different verification methods to different segments of data. High-cost verification methods are applied only to segments where they provide the most value, while lower-cost methods handle the majority of data records. This segmentation allows the system to achieve high overall verification accuracy without incurring the full cost of applying all verification methods uniformly across all records.
2Reliability
If high-cost verification methods are used for all data, then verification accuracy is improved, but resource consumption increases
Solution Approach 1:
The patent implements local quality by assigning different verification method qualities to different data records based on their characteristics and value. High-value or high-risk data records receive high-cost, high-accuracy verification methods, while lower-value records receive more economical verification approaches. This ensures that verification resources are concentrated where they provide the greatest reliability improvement.
3Loss of energy
If data is segmented and different verification methods are applied to each segment, then cost-effectiveness is improved, but system complexity increases
Solution Approach 1:
The patent implements self-service through an automated AI module that autonomously performs data segmentation, selects appropriate verification methods for each segment, and executes the verification process without requiring manual intervention. The system automatically learns from verification results and adjusts its segmentation and method selection strategies, reducing the operational complexity burden despite the sophisticated segmentation logic.
4Productivity
If AI dynamically adjusts verification method usage, then business objectives are met more effectively, but computational requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-training the AI module with historical verification data and results before deployment. The AI learns optimal segmentation strategies and verification method selections in advance, allowing it to make rapid, accurate decisions during actual verification operations. This pre-learning phase reduces the computational burden during real-time verification, as the AI can leverage its trained knowledge rather than performing complex real-time analysis for each data record.
Data Source
AI summary
Embodiments are directed to data verification of business or consumer data. Certain embodiments include a data verification system that receives or selects data to be verified, selects one or more verification methods to verify, update, and/or append/enhance the data. The data verification system may verify the data with one or more data verification methods, either alone or in combination. The methods may include a web-crawling verification method, an agent web verification method, a call verification method, a direct mail method, an email method, an in-person verification method, or other methods. The system has the ability to, automatically or manually, (1) blend automatic and manual segmentation of records or elements by criteria such as industry type, best times of day/month/year to verify, update, or append, cost, and level of importance (2) select the best verification processing method(s), and (3) manage the results and properly verify, update, append/enhance records.