How Graph Databases Stop E-commerce Fraud in Real Time

Graph database technology is able to detect patterns that arise around e-commerce fraud scenarios and put an end to them in real-time, before a fraudster can inflict significant damage. E-commerce fraud often involves large numbers of users with transactions originating from the same IP address, shipments using the same credit card, or multiple credit cards using the same address. The pattern inside the graph, discovered by walking relationships between disparate pieces of information, serves as strong indicating signals of an e-commerce fraud event. Graph databases are designed to carry out pattern discovery in real-time across these datasets and can uncover schemes before they inflict significant damage, with triggers including login, placing an order, or registering a new credit card.

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