neo4j-product-examples/demo-fraud-detection-with-p2p
Exploring Neo4j and Graph Data Science for Fraud Detection
This project helps fraud analysts investigate and predict fraudulent activity within peer-to-peer payment platforms. It takes anonymized transaction data and relationships between accounts, then applies graph analytics to uncover hidden fraud rings, identify suspicious accounts, and flag high-risk transactions. Fraud investigators and risk managers would use this to enhance their detection capabilities.
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Use this if you are a fraud analyst or risk manager dealing with P2P payment data and need to uncover complex fraud patterns that traditional methods miss.
Not ideal if you are looking for a plug-and-play fraud detection solution without needing to understand or engage with graph analytics.
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82
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Jupyter Notebook
License
Apache-2.0
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Last pushed
Jun 12, 2023
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