AI-Driven Cybersecurity in FinTech & Cloud: Combating Evolving Threats with Intelligent Defense Mechanisms

Abstract

The increasing reliance on cloud computing in the financial technology (FinTech) sector has introduced sophisticated cyber threats that challenge traditional security frameworks. AI-driven cybersecurity has emerged as a transformative approach, leveraging machine learning, deep learning, and predictive analytics to enhance threat detection, response automation, and fraud prevention. This study explores the evolving threat landscape in FinTech and cloud security, highlighting vulnerabilities such as phishing, ransomware, API exploits, and insider threats. It examines the role of AI-powered security mechanisms, including Zero Trust Architecture (ZTA), automated Security Information and Event Management (SIEM) systems, and behavioral analytics, in mitigating cyber risks. Additionally, the research addresses challenges in AI security, such as adversarial machine learning attacks, algorithmic bias, regulatory compliance gaps, and the ethical implications of AI-driven decision-making. Future advancements, including quantum- safe AI encryption, blockchain-integrated security frameworks, and AI-driven collaborative threat intelligence, are analyzed for their potential to enhance cybersecurity resilience. The study concludes with recommendations for strengthening AI-based security strategies in FinTech and cloud environments, emphasizing the importance of transparency, regulatory alignment, and continuous innovation. By adopting AI-powered cybersecurity solutions, financial institutions and cloud providers can proactively defend against evolving cyber threats, ensuring the integrity and security of digital financial infrastructures.