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.