Leveraging AI and Machine Learning to Detect and Prevent Fraud in Digital Wallet Transactions

##plugins.themes.academic_pro.article.main##

Arooj Basharat
Anas Raheem

Abstract

The rapid adoption of digital wallets has revolutionized financial transactions, offering convenience and accessibility. However, this shift has also introduced vulnerabilities to fraud, necessitating robust detection and prevention mechanisms. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies in addressing these challenges. This paper explores the application of AI and ML in identifying fraudulent activities in digital wallet transactions. We present a detailed analysis of fraud typologies, methodologies for detection, and experimental results from model implementations. The study demonstrates the efficacy of these technologies in minimizing financial losses while enhancing transaction security. Our findings underline the critical role of advanced algorithms in safeguarding digital financial ecosystems.

##plugins.themes.academic_pro.article.details##

How to Cite
Arooj Basharat, & Anas Raheem. (2025). Leveraging AI and Machine Learning to Detect and Prevent Fraud in Digital Wallet Transactions. Pioneer Research Journal of Computing Science, 2(3), 18–25. Retrieved from http://prjcs.com/index.php/prjcs/article/view/96

Similar Articles

1 2 3 4 5 6 > >> 

You may also start an advanced similarity search for this article.