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Monday, August 8, 2016

Graph Advantage: Fraud Detection

Financial institutions and insurance firms with traditional fraud detection capabilities lose billions of dollars to fraud. Traditional approaches in detecting fraud play a critical aspect in minimizing financial losses. However, an increasing number of fraudsters have created different methods to avoid being discovered. In order to gain the upper hand again these financial institutions are need to combine the traditional subject matter expertise of an analyst with enhanced exploration and discovery capabilities enabled through a highly connected data set in a graph database.

Real-Time Fraud Detection with Graph Databases

Graph databases provide new ways of unearthing fraud rings and other high-tech scams with incredibly precision. This predictive assist, allows your company to focus on the important data necessary to uncover and halt advanced fraudulent actives in real-time. At the same time, a graph database can offer insight based on data relationships to help you create advanced fraud detection systems according to connected intelligence.

Why Neo4j is Effective at Detecting Fraud

With fraudulent activity becoming more sophisticated and disconnected, enterprises have augmented their fraud-detecting capabilities with Neo4j to discover fraud rings and other scams accurately and in real-time. Regardless if it’s money laundering, e-commerce fraud, or bank fraud, Neo4j aids you in

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