About the Client

Our client is a privately owned financial institution based in Oklahoma City. It is one of the largest privately owned bank in the United States with $20+ billion in assets.

Business Requirement

  • The bank deals with fraud analysis and keeps track of money laundering. There is a need of a system which could be easy to use and find AML cases across transactions.
  • Finding suspicious accounts and activities is essential.
  • Grouping multiple transactions and track the sender is a challenge.
  • Analyzing and detecting fraud patterns.

Our Solution

  • Machine Learning and Rules Based (In time & historical) fraud detection patterns are used.
  • Pattern Repository is also created for future reference.
  • Ellicium developed a python-based system to automate this process.
  • Red flags are used to analyze the fraud based on conditions.
  • Dashboard for analysis is prepared.

Process Flow


Business Outcomes

  • Recognizing the sender and the receiver to analyze the date and time.
  • Graphs for analyzing of inbound and outbound score to predict inlier or outliers (suspicious cases).
  • Download the result of execution either combined or individual.
  • Stop excessive withdrawal of money by flagging accounts.
  • Manual efforts are reduced.