Summary
Neo4j Graph Data Science (GDS) integrates with the industry leading Neo4j graph database and makes graph algorithms and machine learning more easily accessible to data scientists. In this webinar we will explain how to combine Linkurious Enterprise’s graph visualization and analytics capabilities and Neo4j GDS to detect suspicious communities, enrich your machine learning models, identify nodes that play a critical role in a network, and more.
Agenda:
- How fraud networks commit BNPL and consumer credit fraud
- How to use graph analytics to detect synthetic identities and fraud rings
- How to combine real-time risk scoring and forensics investigations effectively
- What is Graph Data Science (GDS)
- How to apply Neo4j GDS in fraud detection, entity resolution or network optimization
- How to easily integrate Linkurious Enterprise, Neo4j and Neo4j GDS
- Demo: Efficiently detecting complex fraud networks
Speakers
Jean Villedieu
Jean is the co-founder and Sales Director at Linkurious. Over the years, he has worked with a wide range of Fortune 500 companies and government agencies to help them find insights in complex connected data. Previously, he worked in the consulting industry. Jean double-majored in both political sciences and competitive intelligence.
Bernard Semann
Bernard is part of the solutions engineering team at Linkurious. He joined Linkurious owing to his passion helping organizations explore data silos. He worked as a research and development engineer for online banking solutions and virtual reality sectors. Bernard graduated as PhD in computer science in 2018 following his engineering studies.