The Role of AI in Preventing Return Fraud: A Study of Amazon’s Flexible Return Policy and Consumer Behavior

Purpose – The purpose of this study is to examine the role of Artificial Intelligence (AI) in ‎identifying and preventing return fraud on Amazon. It also seeks to explore the behavioral ‎patterns and motivations behind the exploitation of Amazon’s flexible return policy by ‎consumers.‎ Design/Methodology/Approach – This research employed a quantitative approach using ‎structured online surveys distributed to Amazon customers with return experience. The data were ‎analyzed using descriptive statistics, chi-square tests, and regression analysis. Reliability was ‎tested through Cronbach’s Alpha to ensure consistency of constructs such as AI awareness, ‎policy perception, and return behavior.‎ Findings – The study found that higher awareness of AI monitoring significantly reduces the ‎likelihood of return fraud. Demographic factors such as age and shopping frequency were also ‎found to influence return behavior. Perceptions of policy leniency increased the chances of policy ‎exploitation. Overall, AI was viewed positively when implemented with transparency and ‎fairness.‎ Originality/Value – This study contributes to the emerging body of literature on AI applications ‎in fraud prevention within e-commerce, particularly in return management. It provides actionable ‎insights for online retailers, especially Amazon, on leveraging AI ethically to enhance fraud ‎detection while maintaining customer trust and satisfaction‎.