Dynamic Data Routing Based on Source Error Probability
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Solution Overview
Problem
Financial instrument processing systems face challenges in efficiently routing data processing jobs among different channels based on source-error probabilities, leading to potential errors and inefficiencies in automated versus manual processing.
Innovation Solution
A data processing system that determines source error probabilities and routes data processing items between automated and manual networks dynamically, considering multiple sources and adjusting the level of scrutiny based on combined error probabilities and type of source.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data processing items are routed to automated data processing networks, then processing speed and productivity are improved, but error probability increases
Solution Approach 1:
The system dynamically adjusts routing decisions based on real-time error probabilities associated with different data sources. The routing is not static but adapts to changing conditions, selecting between automated and manual processing channels based on current source reliability metrics.
Solution Approach 2:
The system changes the routing parameter (automated vs manual processing) based on the error probability parameter. When source error probability exceeds a threshold, the system switches from automated processing to manual processing, effectively using parameter changes to resolve the contradiction between speed and reliability.
2Reliability
If data processing items are routed to manual data processing networks, then error probability is reduced, but processing speed and productivity decrease
Solution Approach 1:
The system dynamically selects between manual and automated processing based on source error probability. Manual processing is not always applied but only when the error probability threshold is exceeded, allowing the system to optimize between reliability and productivity on a per-item basis.
Solution Approach 2:
The system uses parameter changes to switch between processing modes. When source error probability is low, automated processing is used for high productivity; when error probability is high, manual processing is used for high reliability. This conditional parameter change resolves the contradiction.
3Measurement precision
If source error probability is determined and routing decisions are made dynamically, then processing accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the data processing flow into distinct components: source identification, error probability determination, routing decision, and execution. This segmentation allows each component to be independently optimized and managed, reducing overall system complexity while maintaining routing accuracy.
Solution Approach 2:
The system introduces an intermediary routing layer that sits between data sources and processing networks. This intermediary component determines source error probability and makes routing decisions, simplifying the overall system architecture by centralizing the decision-making logic in a dedicated module.
Data Source
AI summary
Systems, computer program products, and methods are described herein for routing data processing among different processing channels based on source-error probabilities. The present invention is configured to receive a data processing job comprising at least one data processing item; determine a first source of the at least one data processing item; determine a source error probability associated with the first source; and based on the determined source error probability, route the data processing item for data processing to an automated data processing network or a manual data processing network.