In this lightning talk, Shaurya Agrawal will demonstrate how Neo4j’s graph database technology can revolutionize credit risk management for Financial and FinTech firms by uncovering hidden relationships between entities. Using a real-world scenario where Company A, Company B, and Company C, are subsidiaries, with varying ownership, under a common parent, you will see how traditional systems often miss these indirect connections—potentially underestimating aggregate exposure and risk. With Neo4j, you will learn how to model and visualize complex corporate hierarchies, instantly revealing cross-entity dependencies and shared liabilities.

Attendees will discover how graph queries can surface risk concentrations, identify circular ownership, and support more informed credit decisions. This session will show you how leveraging Neo4j’s relationship-first approach enables smarter, faster risk assessment—empowering you to move beyond the limitations of legacy, table-based systems.