Cyber Risk Quantification for SMEs: AI-Based Approaches to Enhance Resilience

Abstract

Small and medium-sized enterprises (SMEs) are particularly susceptible to cyber threats, and it has been discovered that SMEs are nearly 60 times more vulnerable to a breach than large corporations, and that the average cost of a data breach globally is nearly fourfold in 2022 to USD 4.35 million. Despite their contribution to the economy of nations across the globe, SMEs normally lack the dedicated cybersecurity infrastructure and resources that larger organizations can easily purchase, which makes them highly vulnerable to operational and financial interference. The present paper presents a theoretically-grounded and framework-based study, which investigates the quantification of cyber risks with the use of AI on SMEs. The proposed structure will introduce the application of machine learning and predictive analytics within the risk scoring model into the framework in order to enable SMEs detect vulnerabilities, anticipate events and transform the risks linked to cybersecurity into a measurable business and financial impact. The model allows the leaders of the SMEs to possess actionable decision support to run and simultaneously provide insurers with clear and data-driven information concerning the organizational risk. In addition, the framework would focus on AI-driven risk scorecards that would contribute to the efficiency of the operations and aid in the utilization of cyber insurance. The study is also internationally relevant and it assists to build SME resilience by demonstrating how AI can deal with the resource shortage and more exposure to digital threats by proactively and scalably using competitiveness protection in a more interconnected economy.