Distributed Transaction Analysis System with Serving Container Manager
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Solution Overview
Problem
Existing fraud detection systems struggle to efficiently analyze transactions in real-time, especially as fraudulent transactions become more sophisticated and intelligent, requiring adaptive and advanced predictive models.
Innovation Solution
A distributed transaction analysis system that utilizes a serving container manager (SCM) to control analysis groups and a codec for full-text division, enabling rapid transaction analysis and adaptive resource allocation for artificial intelligence engines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If full-text transaction analysis is performed using traditional centralized systems, then analysis completeness is maintained, but analysis speed and real-time processing capability deteriorate
Solution Approach 1:
The patent divides the full-text transaction analysis into multiple segments by creating separate analysis groups (first analysis group, second analysis group, etc.) that process different portions of the transaction text concurrently. Each analysis group contains AI engines specialized for specific analysis tasks, enabling parallel processing that improves analysis speed while distributing system complexity across multiple independent units.
2Reliability
If more AI engines are deployed to improve analysis accuracy, then detection capability improves, but computing resource consumption and system cost increase
Solution Approach 1:
The patent implements local quality by creating analysis groups with specialized AI engines tailored to specific analysis requirements. Each analysis group contains AI engines optimized for particular transaction analysis tasks rather than using generic engines throughout. This specialization improves detection capability for specific fraud patterns while reducing overall computing resource consumption by deploying only the necessary specialized engines for each analysis group.
3Loss of time
If transaction analysis is performed in real-time, then fraud detection timeliness improves, but processing complexity and computational load increase
Solution Approach 1:
The patent implements dynamics by creating a flexible analysis group management system where the serving container manager can dynamically add or remove analysis groups based on real-time transaction characteristics. The system can adaptively deploy additional AI engines when complex transactions require enhanced analysis or reduce resources when simpler transactions are processed, enabling real-time analysis while managing processing complexity through dynamic resource allocation.
Data Source
AI summary
A method of controlling a distributed transaction analysis system for analyzing a transaction on the basis of a distributed workflow and a device for performing the method can include controlling, by a serving container manager (SCM) for the distributed transaction analysis system, a plurality of analysis groups included in a worker part and controlling, by the SCM for the distributed transaction analysis system, full-text division of a codec.