The financial services sector faces unprecedented cybersecurity challenges, with attackers increasingly leveraging sophisticated techniques including phishing, business email compromise (BEC), and ransomware attacks. This research investigates the deployment of artificial intelligence and machine learning technologies to enhance real-time threat detection and response capabilities across banking and fintech environments. Through comprehensive analysis of contemporary AI-powered cybersecurity frameworks and examination of implementation strategies, this study demonstrates how financial institutions can significantly improve their cyber resilience posture. The research includes a prototype system architecture that integrates federated learning and blockchain technologies to address the unique security requirements of the financial sector. Findings indicate that AI-driven threat detection systems can reduce response times by up to 85% while improving accuracy rates to 97.3% for known threat patterns. This study contributes to the growing body of knowledge on AI applications in financial cybersecurity and provides actionable insights for industry practitioners and policymakers.
Tolulope Awobeku (Tue,) studied this question.