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Graph-based intelligence analysis

For decades, the intelligence community has been collecting and analyzing information to produce timely and actionable insights for intelligence consumers. But as the amount of information collected increases, analysts are facing new challenges in terms of data processing and analysis. In this article, we explore the possibilities that graph technology is offering for intelligence analysis.

Stolen credit cards and fraud detection with Neo4j

Have you ever had your credit card stolen? It is not an uncommon situation. If it happens to you and you’re lucky, your bank will end up paying for the operations made with the credit card. But what happens behind the scene? Do criminals get caught? In this post, we see how graph technology like […]

Insurance Fraud Investigation using Linkurious

  In the US alone, insurance fraud costs companies between 40 and 80 billion dollars each year. Being able to detect fraud schemes before fraudsters steal anything is critical for insurance companies. Yet, the detection and investigation processes remain difficult for these institutions. Most of them simply lack the appropriate tools to detect and investigate complex […]

Fighting eCommerce fraud with graph technology

Ecommerce fraud is growing quickly, creating new challenges in terms of prevention and detection. As merchants gather more and more information about customers and their behaviors, the key element in the fight against fraud is now to draw on the connections within the data collected to uncover fraudulent behaviors. In this post, we explain why […]

Graph-based Enterprise Architecture Management

Part of this article was initially published on Neo4j’s blog.  Today, Enterprise architects are required to deliver insights quickly and make sense of large amounts of enterprise data (business knowledge, application information, technology assets, etc).

Reinforcing AML systems with graph technologies

Fighting financial crimes is a daily battle worldwide. Organizations have to deploy intelligent systems to prevent and detect wrongdoings, such as anti-money laundering (AML) control frameworks. We’ll see in this blog post how graph technologies can reinforce these systems. Using graph technologies to fight financial crimes In today’s complex economy, law enforcement and financial organizations fight against […]

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