Effectiveness of ai in detecting financial fraud: a case study of digital payment systems

The rapid growth of digital payment systems has transformed the global financial landscape, but it has also increased the risk of sophisticated financial frauds. Artificial Intelligence (AI) has emerged as a critical tool for enhancing fraud detection capabilities, offering real-time analysis, pattern recognition, and predictive modeling that surpass traditional rule-based systems. This study examines the effectiveness of AI in detecting financial fraud within the context of digital payment systems, using both quantitative survey data and qualitative insights. Data were collected from 120 respondents, including industry professionals and digital payment users, to assess AI adoption levels, trust in fraud detection methods, and perceived effectiveness. Results indicate that 47% of organizations currently employ AI tools for fraud detection, with AI-based systems gaining higher trust (35%) compared to traditional methods (26.67%). Findings reveal that AI demonstrates superior adaptability to evolving fraud patterns, yet challenges remain in terms of implementation cost, data privacy concerns, and user awareness. The study concludes that while AI significantly enhances fraud detection efficiency and accuracy in digital payments, its optimal effectiveness depends on integrated approaches combining AI, regulatory compliance, and user education. The implications of this research are relevant for policymakers, financial institutions, and technology developers seeking to strengthen fraud prevention strategies in the digital era.