Financial Risk Control Mapping Optimization Solution
Key measures to improve analytical efficiency:
- Index Optimization: Create composite indexes for key attributes
CREATE INDEX ON :Transaction(amount, time) - Graph Algorithm Selection: For different scenarios:
- Fraud detection: using
graph.algorithm.community()Identification of suspicious groups - Money-laundering analysis: applications
graph.algorithm.pagerank()Identify funding pivot nodes
- Fraud detection: using
- Mixed queries: Combining semantic filtering and time windows
WHERE r.relation_type=''transfer'' AND r.date BETWEEN date()-duration(''P1M'') AND date()
Performance tip: Enabling is recommended for very large-scale mappinggraph.enable_cache()Cache common query paths.
This answer comes from the articleGraphiti: dynamic knowledge graph construction and query tool (time-aware long memory scheme)The
May not be reproduced without permission:AI productivity tools " How to optimize the efficiency of relational network analysis in financial risk control scenarios?
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