Containerized Transaction Management System with Buffer Logic
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Solution Overview
Problem
Current personal financial management solutions fail to provide comprehensive, real-time, and dynamic data to end users, lacking in categorization accuracy and integration of transaction management with asset and liability linkages, which leads to inefficient client lifestyle management.
Innovation Solution
A containerized transaction management system that categorizes transactions using a three-tiered approach (client rules, system rules, and default categorization) and assigns them to containers, linking transactions to assets or liabilities, while employing machine learning for enhanced categorization and linkage suggestions, and using container logic to handle transfer and credit card payment transactions by placing them in buffers until matching counterparts are identified.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If transactions are categorized using multiple tiers (client rules, system rules, default categorization), then categorization accuracy is improved, but system complexity increases
Solution Approach 1:
The categorization system is divided into three distinct tiers: client rules (customizable by users), system rules (pre-configured categories), and default categorization (automated fallback). This segmentation allows each tier to handle specific types of transactions appropriately, improving accuracy while maintaining manageable complexity through modular organization.
Solution Approach 2:
The patent introduces an intermediary classification layer that sits between raw transaction data and final categorization. This intermediary tier processes transactions through multiple evaluation stages, allowing complex categorization logic to be applied systematically without overwhelming the system architecture.
2Measurement precision
If transfer and credit card payment transactions are placed in buffers awaiting counterpart identification, then transaction matching accuracy is improved, but processing time increases
Solution Approach 1:
Transactions identified as transfers or credit card payments are placed in buffers with predetermined matching criteria established in advance. The system proactively searches for counterpart transactions using pre-defined parameters (amount, timing, related accounts), allowing accurate matching without delaying final transaction processing unduly.
Solution Approach 2:
The buffer system dynamically adjusts its operation based on transaction flow and matching success rates. Transactions are held in buffers only for necessary durations, with the system continuously evaluating whether counterpart matches have been found, allowing flexible time management that balances accuracy with processing efficiency.
3Loss of information
If a comprehensive client dashboard is provided with real-time transaction data and categorization, then user insight quality is improved, but data processing requirements increase
Solution Approach 1:
The system extracts and presents only the most relevant transaction information and categorization insights to users through the dashboard, rather than displaying all raw data. This selective extraction provides comprehensive user insight while reducing the processing burden by focusing on key metrics and categorized summaries.
Solution Approach 2:
The dashboard provides real-time updates and comprehensive categorization information selectively, updating users with full detail when necessary while using summarized views for routine monitoring. This partial action approach ensures users receive complete information when needed without continuously processing and transmitting all possible data points.
Data Source
AI summary
A containerized transaction management method is disclosed. The method comprises categorizing, by a transaction categorizer, a transaction as a credit card payment transaction or a transfer transaction and determining, by a container assigner, whether a counterpart transaction is identified based on applying container logic. The method also comprises placing, by the container assigner, the transaction in a buffer based on a flag of the container if no counterpart transaction is identified and periodically retesting, by the container assigner, the transaction to determine if a new matching counterpart transaction becomes available within a predefined amount of time. The method additionally comprises providing, by a display engine, a client dashboard to a user device for display on a graphical user interface (GUI) of the user device, wherein the client dashboard comprises a graphical representation that does not include the transaction in the buffer.