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Tag Publications: fraud detection

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 […]

Linkurious brings DataStax Enterprise Graph technology “to life”

Linkurious now fully supports DataStax Enterprise Graph. We’re very excited to partner with DataStax to help their clients find value in their data and enable them to use it for fraud detection, cyber security and intelligence analysis. DataStax Enterprise is a graph database solution based on the open source Apache Cassandra architecture. Datastax provides support […]

Fraud detection in retail

Fraud detection is all about connecting the dots. We are going to see how to use graph analysis to identify stolen credit cards and fake identities. For the purpose of this article we have worked with Ralf Becher, irregular.bi. Ralf is Qlik Luminary and he provides solutions to integrate the Graph approach into Business Intelligence […]

Investigating a money laundering scheme

Following the money is a good way to fight criminal organizations but it can be a big challenge. Gangs, white-collar criminals or terrorists can create complex circuits to launder their money. Investigators have to map these circuits in order to bring down the criminals and graphs can help them! The challenges of investigating money laundering schemes According […]

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