Check Image Fraud Detection using Deep Learning Models

Our project aims to tackle the persistent issue of bank check fraud by using advanced deep learning technologies. By developing a system that can automatically detect fraudulent alterations in check images, we seek to enhance the security and reliability of financial transactions. This project is a collaboration with Verafin Inc., a leading provider of fraud detection solutions. The intern will work on creating and training deep learning models to identify signs of check fraud, such as tampered signatures or altered amounts. The results of this project will help Verafin improve their fraud detection capabilities, leading to better protection for financial institutions and their customers. Additionally, this project will contribute to Canada’s leadership in financial technology, promoting economic stability and trust in the financial sector.

Faculty Supervisor:

Karteek Popuri;Lourdes Peña-Castillo

Student:

Partner:

NASDAQ Canada Inc

Discipline:

Computer science

Sector:

Finance and Insurance; Information and Communication Technology; Artificial Intelligence

University:

Memorial University of Newfoundland

Program: