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Combating Fraud with ArangoDB’s Multi-Model Approach

Fraud Detection with graph
  • A $3.7 Trillion Problem
    Fraud is a growing global issue, costing industries $3.7 trillion annually as fraudsters become increasingly sophisticated in hiding activities.
  • Beyond Traditional Detection
    Conventional methods rely on discrete data and often miss critical patterns, leaving organizations exposed to undetected fraud rings and identity theft.
  • Multi-Model Technology to the Rescue
    ArangoDB’s multi-model capabilities allow companies to analyze data from multiple perspectives, detecting hidden fraud patterns across large-scale datasets.
  • Inside the White Paper
    Learn how to convert relational data into multi-model graphs, utilize fraud detection queries in ArangoDB Query Language (AQL), and implement fraud detection at scale with graph technology.

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