Transaction Exchange Platform Duplicate Detection
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Solution Overview
Problem
Current transaction processing systems face challenges in efficiently detecting and preventing duplicate transactions, leading to delays and increased costs due to errors in transaction files, particularly in systems like NACHA files, where manual corrections are time-consuming and prone to errors.
Innovation Solution
A transaction exchange platform utilizing a streaming data platform and microservices to perform field-by-field checks and machine learning-based analysis to identify and correct duplicate transactions, generate unique identifiers, and automate remediation of rejected transactions, ensuring efficient processing and reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If spreadsheet row checking is used to detect duplicate transactions, then duplicate transactions can be identified, but the process becomes time-intensive and prone to user errors
Solution Approach 1:
The patent replaces manual spreadsheet row checking with an automated electronic system that uses database queries and algorithms to detect duplicate transactions. This substitution eliminates manual user errors and significantly reduces processing time while maintaining or improving detection accuracy.
Solution Approach 2:
The system performs self-service by automatically detecting, flagging, and preventing duplicate transactions without requiring manual intervention. The electronic data processing system autonomously compares transactions against existing records and takes corrective action, eliminating the need for time-consuming manual review.
2Ease of manufacture
If database integrity checking with unique identifiers is used, then transaction uniqueness can be enforced, but duplicate transactions may still be missed because each transaction receives a unique identifier
Solution Approach 1:
The patent implements preliminary action by performing duplicate detection checks before transactions are submitted to the database. The system proactively identifies potential duplicates using multiple criteria (transaction type, amount, dates, parties) and prevents them from being processed, rather than relying solely on post-submission unique identifier checks.
Solution Approach 2:
The system changes the parameters used for duplicate detection from relying solely on system-generated unique identifiers to using multiple transaction-specific parameters such as transaction type, amount, dates, and party information. This multi-parameter approach significantly improves duplicate detection reliability while maintaining processing simplicity.
3Reliability
If manual correction of transaction file errors is performed, then errors can be corrected, but the process is time-consuming and delays transaction processing
Solution Approach 1:
The patent replaces manual error correction with automated electronic validation and correction systems. The system automatically validates transaction files against required formats and standards, identifies errors, and performs corrections without human intervention, thereby maintaining high accuracy while preserving processing throughput.
Solution Approach 2:
The system performs preliminary validation and error correction before transactions are submitted for processing. By proactively identifying and correcting format errors, validation errors, and duplicate transactions in advance, the system ensures high accuracy without causing delays during the actual processing phase.
4Reliability
If transaction files are re-worked and re-submitted after errors are found, then correct transactions can be processed, but all transactions in the file are delayed
Solution Approach 1:
The patent implements comprehensive preliminary validation that checks all transactions in a file before submission. By identifying and correcting errors, removing duplicates, and validating formats in advance, the system ensures that transactions are ready for immediate processing without requiring re-work or re-submission, thereby eliminating delays.
Solution Approach 2:
The system provides immediate feedback on transaction validation results and error conditions. This real-time feedback allows the system to automatically adjust and correct issues before submission, preventing the need for delayed re-submission and ensuring continuous processing flow.
Data Source
AI summary
Aspects described herein may relate to a transaction exchange platform using a streaming data platform (SDP) and microservices to process transactions according to review and approval workflows. The transaction exchange platform may receive transactions from origination sources, which may be added to the SDP as transaction objects. As the transactions are received, the transactions may be analyzed to detect duplicate transactions and/or errors in the transactions. The transaction exchange platform may take steps to remediate transactions that are recognized as duplicates or predicted to generate one or more errors. Similarly, the transaction exchange platform may take steps to remediate transactions that are rejected by a clearinghouse.