Application of Different Machine Learning and Data Mining Algorithms in the Detection of Financial Fraud

Detection of financial fraud is a priority for financial institutions. There are a variety of techniques and models that can be used to address the problem of financial fraud. However, as fraudsters are becoming more inventive and adaptive, they have been able to penetrate the conventional protective methods. This is one of the main reasons for the growth in financial fraud activity, regardless of the efforts of financial institutions and government and law enforcement agencies. This project investigates the use of artificial intelligence and machine learning algorithms to detect financial fraud.

Faculty Supervisor:

Sohrab Zendehboudi


Mohammad Mahdi Ghiasi


Verafin Inc.


Engineering - computer / electrical


Finance, insurance and business


Memorial University of Newfoundland



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