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Volume 4 Issue 5
September-October 2026
| Author(s) | Ch. Keerthi, Dr. B. Nandini |
|---|---|
| Country | India |
| Abstract | Digital payment systems have become the backbone of global commerce, but their rapid expansion has been paralleled by a sharp rise in payment fraud, identity theft, and cyber-enabled financial crime. This paper examines the role of Artificial Intelligence (AI) in enhancing the security and fraud-detection capability of digital online payment systems, drawing on recent industry reports, regulatory data, and empirical machine learning studies. The study adopts a descriptive-analytical approach, synthesising secondary data from central bank publications, market-research reports, and peer-reviewed comparative studies of algorithms such as Random Forest, Artificial Neural Networks, Support Vector Machines, and Gradient Boosting Results show that AI-powered fraud detection tools, such as the ensemble method Random Forest, consistently outperform their human counterparts, with accuracy between 92 and 100 percent in experimental and production environments; real-time behavioural analytics, biometric authentication and natural language processing also take fraud protection beyond transaction-level screening to include phishing, social engineering and mule-account detection. The scale of the challenge, as well as the regulatory response to the menace of digital payment fraud, is evident from the Indian Unified Payments Interface (UPI) ecosystem, where the value of digital payment fraud fluctuated despite an over 40 per cent increase in the number of transactions year-on-year, and the Reserve Bank of India's (RBI) MuleHunter.AI initiative. However, the paper still points to certain issues that have not been overcome, such as class imbalance, manipulation by a growing swarm of AI-savvy fraudsters, a lack of explanation, data-privacy restrictions, and disparity in adoption by institutions of varying sizes. The paper concludes that AI plays an essential role in the current payment-security architecture, but it must be complemented with a multi-layered approach that includes technological solutions, regulations, and consumer-awareness initiatives to effectively withstand the ever-changing threat landscape. |
| Keywords | Artificial Intelligence, fraud detection, digital payments, machine learning, cybersecurity, and UPI. |
| Discipline | Other |
| Published In | Volume 4, Issue 5, September-October 2026 |
| Published On | 2026-09-05 |
| DOI | https://doi.org/10.62127/aijmr.2026.v04i05.1510 |

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