基于多源数据的异常交易行为分析研判方法及系统
By constructing a multi-source account association topology and data quality assessment, the problem of low integration efficiency in the collection and analysis of multi-source heterogeneous data is solved, and efficient abnormal transaction identification and evidence analysis are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING JINAN CHUANGSHI TECHNOLOGY CO LTD
- Filing Date
- 2026-01-23
- Publication Date
- 2026-07-17
AI Technical Summary
In traditional criminal investigations, the collection of multi-source heterogeneous data lacks unified standards and automated mechanisms, resulting in low data integration efficiency, biased analysis results, omission of key evidence clues, and inability to effectively identify abnormal transaction paths.
Construct a multi-source account association topology, generate a collection instruction set, acquire and format-convert multi-source heterogeneous fund transaction data, construct a data quality assessment vector, embed credibility weights, form a weighted fund flow network structure, identify abnormal transaction paths, and generate evidence analysis results.
It enables intelligent collection and analysis of multi-source heterogeneous data, improving the comprehensiveness and accuracy of data acquisition, enhancing the accuracy of abnormal transaction identification, and increasing the credibility of evidence chain construction.
Smart Images
Figure CN121981828B_ABST