Building a Cross-Border Knowledge Graph: AI Powered Entity Resolution & Risk Detection

Session Track: Knowledge Graphs & GraphRAG

Session Time: 12:00 pm - 12:30 pm April 15

Session description

Official registries across Central Asia are fragmented, opaque, and difficult to search, making cross-border risk analysis slow and unreliable. In this session, the speaker will present how ClearPic.ai aggregated and normalized data from seven jurisdictions over five years, transforming millions of disconnected records into a unified Knowledge Graph using ML-driven entity resolution and NLP pipelines.

You will learn why traditional exact-match SQL queries fail in real-world investigative scenarios, particularly when faced with transliteration inconsistencies and deliberately introduced errors designed to evade detection. The session will demonstrate how edge-weighted graph traversal and probabilistic matching techniques will enable the discovery of hidden relationships and beneficiaries that deterministic approaches cannot uncover.

The speaker will also explain the economic and operational impact of graph-based intelligence. You will see how replacing manual forensic workflows with graph queries will reduce investigation time from weeks to sub-seconds, increase risk management speed by up to 50×, and improve high-risk entity detection by 40%. By the end of the session, you will understand how knowledge graphs will deliver a level of cross-border transparency and risk visualization that is impossible to achieve with traditional registry tools.