Finance is awash with data, but much of it is subject only to discrete analysis in offline scenarios. In recent years, graph database technology (like Neo4j) has evolved to support connected analysis in real time yielding high-fidelity insights into your domain on demand and at scale.
In this talk we’ll discuss several real-world use-cases from live financial systems covering a broad range of common financial services, backed up by some live examples that show how convenient and powerful graph data can be. In particular we’ll see how graphs detect and prevent credit and insurance fraud, how they enable bank-wide real-time entitlements, how assets are managed and counterparties identified.
The live examples of these use-cases will use Neo4j’s Cypher query language to showcase how rapidly graph queries can be built and how performant they are.
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