AI-Powered Cybersecurity in Financial Institutions: Enhancing Resilience Against Emerging Digital Threats

It is evident that the world of Financial Technology is evolving rapidly, as financial institutions are regularly faced with an escalating threat from increasingly sophisticated cyber-attacks, which artificial intelligence (AI) can help transform the approach to create a much more resilient cybersecurity. In this paper, we study the effectiveness in building robust digital defenses in the financial sector through the usage of AI driven methodologies toward threat detection, incident response, and the ability to do a quick mitigation. This study synthesizes recent manifestations of AI as applied to the financial institutions industry using a rigorous datacentric methodology, evaluating AI applications, including machine learning based anomaly detection, predictive analytics, and automated threat intelligence. Research conducted by Soni et al. (2022) indicates that such AI enhanced cybersecurity can cut the time to react to security incident in more than 40 percent (Soni, 2022), while machine learning algorithms-based systems that been used in high risk environment has made their detection rate as high as 92 percent (Jiang & Yin, 2023). The findings show that AI Powered models enormously reduce risk and improve real time monitoring, while incident response framework is strengthened. In terms of implications for financial sector stakeholders and policymakers, this study’s addition offers crucial insights for an AI–enabled resilient digital infrastructure. We come to a novel conclusion regarding the role of AI in cyber security and propose a set of useful guidelines for financial institutions on how to strengthen security in the face of a changing threat environment.