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Financial Fraud Detection with Graph Data Science

Published by Neo4j

Financial fraud is an increasingly costly problem for every enterprise.

Graph data science turns this problem around by augmenting your existing analytics and machine learning pipelines. The bottom line: Fewer fraudulent transactions and safer revenue streams.

This white paper demonstrates how next-level fraud investigation uses the power of graph technology, including:

  • Why current tactics fail to identify all fraud
  • Why graph data science boosts fraud detection
  • How to improve fraud detection with graph feature engineering
  • How graph analytics benefit even non-technical fraud investigators

Fill out the form to get your copy of Financial Fraud Detection with Graph Data Science: How Graph Algorithms and Visualization Better Predict Emerging Fraud Patterns.

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Related Categories Storage, Email, Network, Software, Storage, Storage, Network Attached Storage (NAS), Enterprise Resource Planning, Compliance, Data Management, Storage Area Network (SAN)

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