Cybersecurity in Financial Services: Addressing AI-Related Threats and Vulnerabilities

In the rapidly evolving landscape of financial services, the integration of Artificial Intelligence (AI) has ushered in a new era of efficiency and innovation. However, this advancement also brings forth a myriad of cybersecurity threats and vulnerabilities that pose significant risks to the integrity and reliability of financial systems. AI-related threats in financial services are not only diverse in nature, encompassing everything from AI-driven phishing attacks to sophisticated algorithm manipulation, but also present unique challenges in detection and mitigation due to their complexity and adaptability. This paper aims to address these critical issues by proposing a comprehensive cybersecurity framework specifically designed to combat AI-related threats within the financial sector. Through an extensive literature survey, the paper identifies key vulnerabilities introduced by AI technologies and reviews current defensive measures, highlighting their limitations. The proposed work introduces novel algorithms and mathematical models that enhance threat detection and vulnerability assessment, tailored for the intricate environment of financial services. Implementation results, supported by empirical data, demonstrate the efficacy of the proposed framework in identifying and mitigating AI-related cybersecurity threats, thereby significantly enhancing the security posture of financial institutions. This research not only contributes to the academic discourse on financial cybersecurity but also offers practical solutions for industry practitioners facing the challenges of AI-related threats.