ARTIFICIAL INTELLIGENCE MODELS AND TOOLS THAT MONITOR AND MONITOR THE SECURITY OF DIGITAL BANKING DATA
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How to Cite

Ramazon o’g’li, . . . S. S. . . (2025). ARTIFICIAL INTELLIGENCE MODELS AND TOOLS THAT MONITOR AND MONITOR THE SECURITY OF DIGITAL BANKING DATA . Confrencea, 10, 222–230. Retrieved from https://confrencea.org/index.php/confrenceas/article/view/1550

Abstract

As digital banking becomes ubiquitous in Uzbekistan, ensuring the
security of sensitive financial data is paramount. This article explores how artificial
intelligence (AI) models and tools are being leveraged to monitor and safeguard
digital banking information. A comprehensive literature review was conducted to
identify the most promising AI techniques and their applications in the Uzbek
banking sector. The results demonstrate that machine learning algorithms, especially
anomaly detection models, are highly effective at identifying fraudulent transactions
and unauthorized access attempts in real-time. Furthermore, natural language
processing tools enable automated analysis of unstructured data like customer
service logs to surface potential security issues. Blockchain technology is also being
piloted to create tamper-proof audit trails.

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Copyright (c) 2024 Shirinov Sherali Ramazon o’g’li