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Graph Feature-Engineering for Scalable Fraud Detection in Commercial Banking
The goal of the research project is to enhance ATB’s fraud detection by incorporating new graph based features. Initially, the project will be focused on figuring out how to use ATB’s data to build graph features. Once the data is processed, these additional graph variables will be used to improve the existing fraud detection machine learning algorithms ATB is currently using. The benefits to ATB will be more proactive fraud prevention and improved customer lifetime value.
Faculty Supervisor:
Matthew Greenberg
Student:
Partner:
ATB Financial
Discipline:
Mathematics
Sector:
Finance and Insurance
University:
University of Calgary
Program:
Accelerate
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