Fraud Detection in Real Time with Graphs

12 May, 2015



Learn how to handle real-time fraud detection with graph technology. Gorka Sadowski, a CISSP from the akalak cybersecurity consulting firm and Philip Rathle, VP of Product for Neo4j, discuss retail banking + first-party fraud, automobile insurance fraud and online payment ecommerce fraud. Graph databases offer new methods of uncovering fraud rings and other sophisticated scams with a high-level of accuracy, and are capable of stopping advanced fraud scenarios in real-time. This provides an enhanced degree of insight, compared to fraud detection algorithms that use basic statistical analysis and pattern recognition. Neo4j is allowing users to develop the next generation of fraud detection systems based on connected intelligence. Read the white paper Financial Fraud Detection with Graph Data Science: https://neo4j.com/whitepapers/financial-fraud-detection-graph-data-science/ #Fraud #FinancialFraud #FraudDetection