College of Business, Westcliff University, United States of America.
Global Journal of Engineering and Technology Advances, 2026, 27(01), 152-157
Article DOI: 10.30574/gjeta.2026.27.1.0097
Received on 15 March 2026; revised on 21 April 2026; accepted on 25 April 2026
The financial industry's digital transformation has fundamentally altered the cybersecurity landscape, introducing both unprecedented opportunities and sophisticated threats. This research examines the critical role of artificial intelligence (AI) in enhancing cybersecurity measures within the financial sector, particularly focusing on emerging digital economy components including cryptocurrency and blockchain technology. Through comprehensive analysis of current literature and industry reports, this study reveals that AI-driven cybersecurity solutions have demonstrated significant efficacy in threat detection and prevention, with machine learning algorithms showing up to 95% accuracy in identifying novel attack vectors. The research indicates that while blockchain technology offers enhanced security through decentralization, it simultaneously introduces new vulnerabilities that require specialized AI-powered defensive mechanisms. Financial institutions implementing integrated AI-cybersecurity frameworks have reported a 60% reduction in successful cyber attacks and a 40% decrease in incident response times. This study concludes that the synergistic application of AI and advanced cybersecurity measures is essential for protecting the evolving financial ecosystem, while highlighting the need for continuous adaptation to emerging threats in the digital economy.
Cybersecurity; Artificial Intelligence; Financial Industry; Cryptocurrency; Blockchain; Digital Economy
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Oluwaseyi Adedeji Adeniyan. The Impact of Cybersecurity and Artificial Intelligence in Combating Cyber Attacks in the Financial Industry: A Comprehensive Analysis of Digital Economy, Cryptocurrency and Blockchain Technology. Global Journal of Engineering and Technology Advances, 2026, 27(01), 152-157. Article DOI: https://doi.org/10.30574/gjeta.2026.27.1.0097.





