Impact of artificial intelligence applications in reducing fraud diamond in commercial banks: A governance context

This study investigates the impact of artificial intelligence (AI) applications, specifically deep learning, neural networks, and machine learning, on reducing fraud in Jordanian commercial banks, using the fraud diamond framework. The study looks at the growing threat of financial fraud, which has evolved with digital banking and increased technological sophistication. A descriptive-analytical approach was used, with data collected via an electronic questionnaire distributed to 216 employees from various departments of Jordanian commercial banks. After removing invalid responses, 190 valid questionnaires were analyzed with SPSS software. The findings show that AI applications have a statistically significant impact on reducing all four dimensions of the fraud diamond: pressure, opportunity, rationalization, and capability. Machine learning had the greatest impact of all AI dimensions, followed by neural networks and deep learning. The study emphasizes banks’ growing interest in using AI for fraud detection and recommends the implementation of more advanced AI tools to improve operational efficiency and financial security. The study provides practical and theoretical insights for banking professionals, policymakers, and academic researchers working on financial fraud prevention in the digital age.