Unifying risk management for AI-driven cybersecurity in finance

Abstract

Artificial intelligence is reshaping organizational strategy, with its influence on the financial services sector continually expanding and introducing novel risks. This study examines the impact of AI-driven cybersecurity on the risk management framework in financial services through a systematic literature review, identifying key themes and research gaps. While existing studies primarily focus on AI-related risks, this study extends this by exploring how organizations can leverage unified risk management strategies to manage the rise of AI-driven cybersecurity in financial services. It aims to unify diverse approaches within the financial sector to develop a robust, scalable risk-management framework applicable across organizations, regardless of size or structure. A common theme among researchers is the need for a comprehensive risk-management strategy, resource collaboration, and data-sharing capabilities to enhance threat detection, analysis, and intelligence sharing. The thematic benefits of this unified approach include collaboration among stakeholders, innovation, holistic risk management, the eradication of fragmented approaches, trust and transparency, reduced cost, and increased efficiency.

Keywords: Risk management framework, artificial intelligence, cybersecurity, financial services, machine learning, critical infrastructure.