AI in Digital Payment Security: An Expanded Study Based on Secondary Data
Keywords:
cybersecurity, transaction monitoring, biometric authentication, fraud detection, machine learningAbstract
Over the past ten years, mobile banking, e-commerce, UPI networks, contactless payments, and real-time settlement systems have all contributed to the rapid evolution of digital payment ecosystems. These systems have also drawn scammers who use sophisticated methods to take advantage of weaknesses, making them a key piece of technology for improving the security of digital payments. This paper analyses existing applications of AI in digital payment security, assesses its efficacy, identifies hazards, and suggests future research directions using secondary data gathered from peer-reviewed journals, industry reports, and research publications. The study identifies the advantages and disadvantages of AI-driven security frameworks, while the enlarged Review of Literature shows the depth of scholarly work in the area. The study concludes that while AI greatly improves fraud detection capabilities, strict control is necessary due to ethical, legal, and technical issues.
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