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Version: 2.13.X

Detecting Bank Fraud With Cogynt Authoring and Workstation

This use case utilizes sample data to investigate bank fraud.

Bank fraud is a blanket term that describes a number of potential financial crimes. Today, we'll focus on a specific type of bank fraud that utilizes mule accounts used in money laundering. The fraudulent activity is appealing to criminals because it is difficult to detect and easy to disguise the movement of money in manageable sums.

Cogynt can help identify this type of fraud with models that pick up on specific activity, such as:

  • Transfers to a fresh account.
  • Transactions below a certain threshold.
  • Repeat transactions.

Other triggers can be combined to form a clearer picture of fraudulent activity, creating a trail for Cogynt to follow. With the right data, Workstation can help visualize these events as networks of linkages.

This use case assumes data is already being exchanged with the Cogynt Data Monitoring tool. This guide has two parts:

  1. Use Hierarchical Event Processing in Cogynt to Uncover Mule Accounts
  2. Build Case Files as Collections For Analysis and Reporting
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