Fraud Detection in E-commerce – A Machine Learning Approach

E-commerce platforms are increasingly threatened by fraud, ranging from identity theft to payment manipulation. Traditional rule-based systems often struggle to identify evolving fraud patterns. This study investigates the application of machine learning (ML) algorithms to enhance fraud detection accuracy in real time. Through a mixed-method approach involving survey data from 100 consumers and interviews with industry professionals, the research evaluates the effectiveness, challenges, and ethical implications of ML-based fraud detection systems.