Methods, devices, storage media, and computer equipment for visualizing reconciliation results
CN122086987APending Publication Date: 2026-05-26GUANGZHOU PINWEI SOFTWARE CO LTD
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GUANGZHOU PINWEI SOFTWARE CO LTD
- Filing Date
- 2026-04-15
- Publication Date
- 2026-05-26
AI Technical Summary
Technical Problem
Existing reconciliation methods have low visualization capabilities, making it difficult to intuitively show the relationship between discrepancies and original data, resulting in low reconciliation efficiency and accuracy.
Method used
By receiving reconciliation results and handling missing values, the key reconciliation fields and their verification thresholds are determined, field-level comparisons are performed, discrepancies are identified, and the sources of discrepancies are highlighted in a visualization table.
Benefits of technology
It achieves a clear correspondence between discrepancies and original data, improves the efficiency and accuracy of reconciliation work, and forms a logically closed-loop and easy-to-operate analysis process.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN122086987A_ABST
Abstract
This application provides a method, apparatus, storage medium, and computer equipment for visualizing reconciliation results. The method includes: receiving reconciliation results and processing missing values to obtain target reconciliation results; determining key reconciliation fields and their corresponding verification thresholds according to pre-configured reconciliation rules; performing field-level comparisons on the target reconciliation results based on the key reconciliation fields and their corresponding verification thresholds to identify discrepancies; and highlighting the discrepancies in a visualization table according to the reconciliation data source. This method overcomes the problems of low visualization and unintuitive data association in existing reconciliation methods, achieves a clear correspondence between discrepancies and original data, significantly improves the efficiency and accuracy of reconciliation work, and forms a logically closed-loop and easy-to-operate reconciliation analysis process.
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