Building Powerful Fraud Detection Applications With Neo4j


Fraud is a huge problem, costing billions across industries worldwide. And with fraudsters quickly adopting new technologies like AI, fraud has become even harder to stop. 

How can you build a powerful fraud detection application that catches these criminals in milliseconds? You need the right tools. If you’re using traditional relational systems and siloed data, it can take weeks or months to detect new fraud schemes – if you ever detect them at all. 

 Join us for this 30-minute on-demand webinar to explore:
  • What fraud looks like today
  • Three ways that relational databases fall short in detecting and preventing fraud
  • How Neo4j graph capabilities help build better fraud detection applications
  • The real-world results of integrating Neo4j into a digital bank’s fraud detection pipeline  
Forget spending endless hours writing SQL or refactoring your database to keep up with the latest fraud tactics. With Neo4j's dev-friendly schema, intuitive data model, and helpful algorithms, you can build a powerful application that quickly detects and helps investigate complex fraud.

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John Stegeman
Product Specialist

John “Steggy” Stegeman is a Senior Graph Database Product Specialist with Neo4j. Prior to joining Neo4j, he held solution architect and consulting roles at Oracle, DXC, Waterline Data, and Hitachi Vantara. John is a self-avowed technology nerd who loves using technology to solve real-world enterprise challenges.