Free Case Study: Real-time Graph Analysis Saves Millions in Fraud Detection Costs

Download this case study: Fraud detection at a fortune 500 financial services company

Analysts at this Fortune 500 financial services company rely on large amounts of data to make fast, accurate decisions regarding fraudulent activity in financial transactions.

With the real-time data analysis and visualization provided by Neo4j, fraud patterns are identified more accurately and manual review time is cut significantly, allowing for an increase in the number of reviewed transactions, and preventing millions worth of fraudulent transactions per year.

This case study will show you how by using the Neo4j graph database, the company is able to:

  • Cut the amount of time for manual data analysis significantly, allowing for a large increase in the number of viewed transactions
  • Provide efficient, in-depth, more accurate fraud analysis that saves the company millions of dollars each year

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