Electronic Data Reconciliation Platform for Commodity Delivery
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Solution Overview
Problem
Current systems for managing information from multiple parties are cumbersome, incomplete, and impractical, particularly in reconciling and confirming data associated with commodity delivery processes.
Innovation Solution
A cloud-based platform that reconciles electronic source, transport, and destination information by normalizing data using predefined schemas, identifying discrepancies, and providing data analytics through a graphical user interface for online collaboration, enabling efficient identification and resolution of delivery discrepancies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual reconciliation processes are used to manage information from multiple parties, then data accuracy can be maintained through human review, but the process becomes cumbersome and time-consuming
Solution Approach 1:
The patent replaces manual mechanical reconciliation processes with an automated electronic system that uses software algorithms to match and reconcile data from multiple sources. The system automatically compares source data, transport data, and destination data using computational methods, eliminating the need for manual human review while maintaining accuracy through systematic data matching and discrepancy identification.
Solution Approach 2:
The reconciliation system performs self-service by automatically identifying and flagging discrepancies without requiring external intervention. The system autonomously processes data from multiple parties, applies reconciliation rules, identifies mismatches, and generates reports, enabling the process to serve itself without continuous human oversight while maintaining data accuracy through built-in validation mechanisms.
2Loss of information
If comprehensive data collection from multiple sources is implemented to ensure complete reconciliation, then data completeness improves, but system complexity increases
Solution Approach 1:
The patent implements a universal reconciliation platform that can handle multiple data sources, formats, and parties through a single integrated system. The system is designed to accommodate various input types (source data, transport data, destination data) and applies consistent reconciliation logic across all inputs, achieving complete data collection without proportionally increasing complexity through standardization and multi-functional design.
Solution Approach 2:
The system introduces an intermediary reconciliation layer that standardizes and harmonizes data from multiple diverse sources before processing. This intermediary layer acts as a mediator that translates different data formats and structures into a common framework, enabling complete data collection from multiple parties while managing complexity through standardized intermediate representation.
3Productivity
If automated reconciliation processes are used to reduce manual effort, then productivity increases, but the ability to handle complex discrepancies decreases
Solution Approach 1:
The patent implements a dynamic reconciliation system that can adapt its processing logic based on the type and complexity of discrepancies encountered. The system uses configurable rules and algorithms that can be adjusted to handle various discrepancy scenarios, allowing automated processing to maintain high productivity while preserving the ability to manage complex cases through flexible, adaptable processing logic rather than rigid fixed procedures.
Data Source
AI summary
Electronic source information is reconciled by normalizing at least some electronic source information, transport information and destination information by applying a plurality of rules to extract the information into at least one schema. At least some of the normalized information is identified to contain at least one discrepancy or missing data record, and reconciliation information is provided in a graphical user interface. Electronic information is received that reconciles the discrepancy or the missing record, and the reconciled and normalized electronic source, transport and destination information is processed to provide data analytics. A report is generated that represents the data analytics and that is output to at least one user. This can occur in one or more implementations of the present application.