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Financial Fraud Detection with Neo4j Graph Data Science

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Financial fraud is growing and it is a costly problem, estimated at 6% of the Global Domestic Product, more than $5 trillion in 2019.

Despite using increasingly sophisticated fraud detection tools – often tapping into AI and machine learning – businesses lose more and more money to fraudulent schemes every year. Graph data science helps turn this pattern around. By augmenting existing analytics and machine learning pipelines, a graph data science approach increases the accuracy and viability of existing fraud detection methods. The end result: Fewer fraudulent transactions and safer revenue streams.

Download this white paper to take a closer look at how your data science and fraud investigation teams can tap into the power of graph technology for higher quality predictions in detecting first-party fraud as well as sophisticated fraud rings.

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