How to Improve Anti-Money Laundering Investigation using Neo4j

Presented by

Joe Depeau, Neo4j

About this talk

Typical anti-money laundering process can be complicated, difficult, lengthy, highly manual, and prone to false positives. The data required for AML investigations is often complex, highly connected, and can come from multiple data sources within an organisation as well as from external providers. Learn how to use Neo4j and the power of connected data along with graph analytics techniques to improve anti-money laundering investigations and compliance. We’ll demonstrate how Neo4j enables faster and more accurate AML investigations, even across diverse and siloed data landscapes.

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Today’s businesses need to generate real-time, valuable insights from their existing data. In this case, the relationships between data points matter more than the individual points themselves. Industry leads are turning to graph databases which treat those valuable relationships (connections) as first-class entities. Neo4j is the world's leading graph database, with native graph storage and processing.