Unveiling the Invisible Threat: Using Machine Learning to Detect Credit Card Fraud

Businesses, including both conventional brick-and-mortar businesses and internet firms, have faced particular hurdles as a result of the COVID-19 epidemic. Online commerce has become more prevalent as a result of the installation of movement restrictions that made it more difficult to make physical purchases. However, a rise in online credit card theft has coincided with this transformation, undermining customer confidence in online transactions. As a result, there is a compelling need to create a machine learning framework that is incredibly strong and can successfully identify almost all cases of fraudulent credit card activity.Our research aims to identify 100% of fraudulent and scam-related credit card transactions, which is an ambitious target. Within the larger category, these fraudulent events are a sizable fraction. Our research focuses on improving data preprocessing as a solution to this.