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Big Data for Fraud Detection and Prevention
Accurately and rapidly detecting fraudulent transactions is primordial in the course of any corporation?s routine operations and essential to its commercial viability, especially a deposit-taking bank. We investigate the use of computer-based techniques to automatically detect fraudulent use of a real banking network. Our goal ultimate goal is to make electronic commerce safer, which will benefit all Canadians.
Faculty Supervisor:
Yuri Lawryshyn
Student:
Pierre Miasnikof
Partner:
Canadian Imperial Bank of Commerce
Discipline:
Engineering - chemical / biological
Sector:
University:
University of Toronto
Program:
Accelerate
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