Credit Card Fraud Detection – Students Research in ML and DL at Durham College

With the new trend of Online Shopping and Online Platforms for transactions, the number of Credit Card based transactions increased tremendously. However, there have been a lot of cases where illegal use of Debit/Credit Cards for making Fraudulent Transactions. Credit card companies have been paying a lot of attention to providing the best service for their customers by having process enhancements and pro-actively looking into transactions before making them through. Global financial losses related to payment cards are estimated to reach $34.66 billion in 2022, according to The Nilson Report, a newsletter that tracks the payment industry. Related to the negative impacts of credit card fraud activities, and financial and product losses, it’s easy for merchants and users to feel victimized and helpless. Machine Learning Models can work well in detecting such Fraudulent actions when they are trained on a large quantity of historical data and then fine-tuned depending on validation and evaluation metrics.

Speaker(s): Priyanka Singh, Devy Ratnasari, Gopika Shaji, Oluwole Ayodele, Saurav Bisht,
Toronto, Ontario, Canada, Virtual: https://events.vtools.ieee.org/m/312336