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Topology Over Predictions: Using Graph Context to Drive Real-Time Lending Decisions
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NODES 2025 - Topology Over Predictions: Using Graph Context to Drive Real-Time Lending Decisions

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What you'll learn

This course includes

  • 51.3 hours of video
  • Certificate of completion
  • Access on mobile and TV

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In this lightning talk, we'll explore a graph-first approach to real-time decision intelligence. Rather than relying solely on ML predictions, we combine multiple contextual graph layers, capturing entity relationships, behavioral signals, and latent structures to generate fully explainable, adaptive decisions in production systems. The architecture fuses Neo4j graphs, vector similarity search, and policy engines into a composable pipeline. We’ll highlight how topology itself, not just features, serves as a signal, enabling systems to optimize outcomes even in sparse or shifting data environments. Speaker: Matthew Watts Resources: Get Started with Aura - https://bit.ly/3LOLrjh Deployment Center - https://bit.ly/4jOelM3 Ground AI Systems and Agents with Neo4j - https://bit.ly/4oVsnyb #nodes2025 #neo4j #graphdatabase #graphrag #knowledgegraph

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