Since the explosive increase in digital economic transactions has increased, so is the possibility of credit card fraud, there is a need for advanced detection technology. The study examines the ability to detect real-time fraud using cloud and artificial intelligence (AI). Examples of artificial intelligence approaches that increase the possibilities of identifying fraudulent activity include machine learning, deviation detection and pattern recognition. Large datasets can be handled using a cloud-based system. Major questions are addressed through hybrid sampling and the use of privacy engineering techniques. The study further highlights support vector machines (SVM) algorithms and Naive Bayes (NB). The real scenario shows how AI systems can provide real-time and less false positive alerts.
