How a Top Bank used Neo4j & Confluent for Fraud Analysis

Streaming data lets us examine business data as either streams or tables, but the connections between the data points add much more value to our data. For this, we need to look at streaming data as a graph. Key use cases include financial fraud investigations, social media analyses, network & IT management, recommendation engines, and knowledge management. In this online talk, we will discuss and demo interactions between streams, graphs, and tables with KSQL, Cypher, GraphQL, Neo4j graph algorithms and Confluent Platform. We will walk through the global bank use case and how they are detecting fraud in real-time using graph analytics and event streaming.