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Credit Card Fraud Detection Using Machine Learning
The National Bank of Canada (NBC) is currently trying to put in place an automatic credit card fraud detection system based on advanced learning algorithms. Credit card fraud happens when someone steals a credit card, credit card information or personal identification number (PIN) and uses it without permission to make a purchase or withdraw money from an automated teller machine (ATM). Credit card fraud is a multimillion dollar problem faced by all financial institutions. Predictive features based on the NBC’s data will be researched, and various learning algorithms used for anomaly detection will be explored. A success in this project will have a direct impact on NBC’s business.
Faculty Supervisor:
Manuel Morales
Student:
Partner:
Banque Nationale du Canada
Discipline:
Mathematics
Sector:
Finance and Insurance; Professional, scientific and technical services
University:
Université de Montréal
Program:
Accelerate
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.