# Exploring Fraud Detection With Neo4j & Graph Data Science — Summary

**URL:** <https://community.neo4j.com/t/exploring-fraud-detection-with-neo4j-graph-data-science-summary/52746>\
**Category:** Community Content & Blogs\
**Created:** [March 2, 2022, 12:06am UTC](https://community.neo4j.com/t/exploring-fraud-detection-with-neo4j-graph-data-science-summary/52746 "2022-03-02T00:06:47Z")\
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**Author:** ![akollegger1](https://sea1.discourse-cdn.com/flex021/user_avatar/community.neo4j.com/akollegger1/32/14828_2.png) [@akollegger1](https://community.neo4j.com/u/akollegger1)\
**Post date:** [March 2, 2022, 12:06am UTC](https://community.neo4j.com/t/exploring-fraud-detection-with-neo4j-graph-data-science-summary/52746/1 "2022-03-02T00:06:48Z")

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Exploring Fraud Detection With Neo4j & Graph Data Science — SummaryA multi-part series with hands-on examples using peer-to-peer (P2P) dataFraud Detection is one of today’s most challenging data science problems. Thankfully, Neo4j Graph Data Science (GDS) offers practical solutions that empower data scientists to make rapid progress in fraud detection analytics and machine learning.SummaryWhether you are responsible for combating financial crimes, online identity ...

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-- Zach Blumenfeld  
Tue, 01 Mar 2022 19:58:09 GMT