Before You Flag It as Fraud, Know Who You’re Dealing With

Banks face significant challenges in fraud prevention and compliance due to the need for precise customer identity resolution in a digital world that demands seamless yet secure experiences. Traditional methods, which often rely on isolated transaction monitoring and static attributes like names and addresses, are insufficient for catching sophisticated fraud schemes and frequently result in false positives that frustrate legitimate customers. To address these shortcomings, banks are increasingly adopting graph-powered entity resolution, which connects fragmented records into a cohesive network that reveals relationships and behaviors, such as hidden collusion and synthetic identities. This approach not only enhances fraud detection by exposing complex fraud networks but also provides clear, explainable evidence trails that satisfy regulatory demands. A real-world application of this technology by a leading multinational bank demonstrated significant reductions in false positives and faster investigations, leading to substantial fraud savings. Tools like TigerGraph enable banks to operationalize this advanced fraud prevention strategy at scale, ensuring both security and regulatory compliance while improving customer trust and satisfaction.