As digital payments become more connected, fraud has evolved beyond isolated transactions into sophisticated networks involving customers, merchants, devices, IP addresses, and payment instruments. Traditional fraud detection systems often struggle to uncover these hidden relationships, making it difficult to stop coordinated fraud before financial losses occur.

Straive addressed this challenge by developing a graph-powered AI solution that models the entire payments ecosystem as an interconnected network. By combining graph analytics, entity resolution, risk propagation, and machine learning, the platform identifies suspicious relationships and fraud clusters in real time. Embedded directly into the live transaction authorization workflow, the solution enables proactive fraud prevention without disrupting payment processing.

Within three months of deployment, the platform reduced fraud losses by 27%, delivering approximately US$3.5 million in projected annual savings. It also improved detection precision, reduced false positives, enhanced investigator productivity, and established a scalable AI framework that continuously adapts to evolving fraud patterns.