This research explores the transformative potential of generative artificial intelligence in enhancing banking security resilience. Through a mixed-methods approach combining quantitative simulations and qualitative assessments, we demonstrate how generative AI models can significantly improve vulnerability detection, incident response times, and business continuity planning. Our findings indicate a 30% improvement in vulnerability detection and a 45% reduction in recovery times, suggesting that AI-driven approaches represent a paradigm shift in banking security frameworks. The study provides a comprehensive framework for implementing generative AI solutions while addressing practical challenges and ethical considerations.
Keywords: Resilience, adaptive strategies, banking security, generative AI, predictive analytics, vulnerability detection
