Abstract
Leveraging Data AI for Cyber Risk Management
Keywords: Cyber risk, AI, Data Science
This presentation explores how data science and AI are transforming cyber risk management, especially in industrial and critical infrastructure environments. It highlights the limitations of traditional cybersecurity investments, which often lack financial justification, and introduces a data-driven, risk-based approach that quantifies cyber threats in business terms. By leveraging internal telemetry, external threat intelligence, and advanced modeling techniques—including AI, Bayesian inference, and stochastic simulations—organizations can estimate the financial impact of cyberattacks, prioritize mitigation efforts, and optimize cyber insurance strategies.
The deck also showcases how vulnerabilities can be translated into dollars at risk, enabling smarter decisions about which threats to address first. Through real-world case studies and simulations, it demonstrates how organizations can reduce exposure, justify cybersecurity budgets, and align technical controls with business outcomes. Ultimately, it presents a practical framework for turning cybersecurity from a guessing game into a measurable, strategic business function.
Talk delivered during the III Semana de la Ciberseguridad. The event took place on March 31, 2025, at the Business and Tech Faculty of UAX in Madrid.
