Transaction Exchange Duplicate Detection With Streaming Adjudication
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Solution Overview
Problem
Existing transaction processing systems face challenges in detecting and preventing duplicate transactions, leading to delays and increased processing costs due to errors in transaction files like NACHA files, which are time-intensive and prone to user errors, and traditional methods like spreadsheet row checking and database integrity checking are inadequate in identifying duplicates.
Innovation Solution
A transaction exchange platform using a streaming data platform and microservices performs field-by-field checks, uses machine learning models to analyze transactions for issues, generates unique identifiers, and includes an adjudication microservice to automate remediation of rejected transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual spreadsheet row checking is used to detect duplicate transactions, then duplicate transactions can be identified, but processing time increases significantly and user errors occur
Solution Approach 1:
The patent replaces manual spreadsheet row checking with an automated system that uses database integrity checking and unique identifiers to detect duplicate transactions. The system automatically compares transactions against existing records in the database, eliminating the need for manual intervention while maintaining high accuracy in duplicate detection.
Solution Approach 2:
The system performs self-service by automatically detecting and preventing duplicate transactions through automated database integrity checks. The unique identifier mechanism enables the system to self-verify transaction uniqueness without requiring manual intervention, thereby reducing processing time while maintaining reliability.
2Reliability
If database integrity checking with unique identifiers is used, then duplicate transactions can be detected, but duplicate transactions with modified identifiers may still slip through
Solution Approach 1:
The system performs preliminary action by validating transaction identifiers and comparing them against existing records before processing. The unique identifier mechanism is established in advance, and the system proactively checks for duplicates during transaction intake, preventing modified or fraudulent identifiers from slipping through.
Solution Approach 2:
The system implements feedback mechanisms where transaction identifiers are validated and compared against database records in real-time. This feedback loop detects and prevents duplicate transactions, including those with modified identifiers, by continuously monitoring and comparing identifier uniqueness against stored records.
3Reliability
If transactions are manually corrected and re-submitted, then errors can be fixed, but processing delays occur and system burden increases
Solution Approach 1:
The patent replaces manual correction processes with automated system validation. The database integrity checking mechanism automatically identifies and prevents duplicate transactions, eliminating the need for manual correction and resubmission. This automated approach maintains transaction accuracy while significantly improving processing speed.
4Measurement precision
If field-by-field checks are performed manually, then duplicate detection can be thorough, but processing time and system resource consumption increase
Solution Approach 1:
The system replaces manual field-by-field checking with automated database integrity validation. The unique identifier mechanism and automated comparison processes perform thorough validation much faster than manual methods, reducing both processing time and system resource consumption while maintaining high validation accuracy.
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.


