March FinCloud: AI in Financial Services for Defensive Security

The integration of Agentic AI and advanced machine learning (ML) in the financial services sector is redefining defensive security practices, enabling organizations to strengthen their ability to respond to cyber threats and ensure regulatory compliance. Agentic AI, with its autonomous decision-making capabilities, combined with ML-driven techniques, is enhancing incident response, policy enforcement, and security operations through automation and real-time adaptation. This abstract explores how Agentic AI and advanced ML are transforming key areas of defensive security, including incident response, playbooks, code reviews, and the creation of security architecture blueprints. These AI-powered solutions facilitate the automation of security processes, such as policy-as-code implementation and the development of configuration baselines that ensure consistency and resilience across complex IT environments. Furthermore, Agentic AI enables dynamic risk assessments by continuously analyzing potential vulnerabilities and suggesting mitigations. By embedding AI and ML into these critical security domains, financial institutions can enhance their proactive defense posture and reduce human error in security operations. The paper also discusses the ethical considerations, regulatory challenges, and best practices for integrating Agentic AI into security frameworks, underscoring its role in creating a more agile, secure, and resilient financial services ecosystem.