Neo4j Live Demo: Smarter Fraud Detection With Graph Data Science

Are you looking to identify fraudulent actors and activities before fraud occurs? Neo4j Graph Data Science makes it easier for data scientists to map and proactively identify fraudulent actors, phone numbers, IP addresses, and more, that help reduce losses.

Join Nick Johnson, Product Marketing Manager for Graph Data Science, for this 20-minute session to understand:

  • What Graph Data Science is
  • Why Graph Data Science is better at solving certain types of problems
  • How data scientists traditionally identify fraud rings and suspicious actors
  • How to visually map and identify fraudulent actors and accounts using Graph Data Science for fraud detection
David Allen
Technology Partner Architect, Neo4j

David Allen is Technology Partner Architect at Neo4j. He is a deeply technical generalist with experience in managing teams and driving towards complex goals. The most fun he has had in his career is when he is learning something new, or trying to figure out how to do something that hasn’t been done before.

 
When not trying to improve something technical, you can usually find David playing guitar or cycling. He loves meeting new people, and has a very keen interest in language and culture and loves to find common ground with other people through travel and music.

Jaime D'Anna
Partner Technical Marketing, Neo4j

Jaime is from the Technology Partner team at Neo4j, with a seasoned career successfully executing channel and product campaigns across industries, geographies and technologies. He has “led the charge” for a number of SaaS, Advanced Analytics and AI solutions from start-ups to larger Enterprise Fortune 200 companies, such as IBM, Oracle and EMC among others. As a graduate of Santa Clara University, Jaime applies his technical, market and industry knowledge enabling today’s organizations to benefit from best-in-class solutions and optimized outcomes from their data.

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