Risk Assessment Models for Autonomous Vehicle Insurance Pricing: A Study on Level 4 and Level 5 Automation in Germany

Abstract

The adoption of Level 4 and Level 5 autonomous vehicles presents significant challenges and opportunities for the insurance industry, requiring a fundamental shift from traditional driver-based risk assessment to AI-driven liability models. This study examines the financial, technological, and regulatory implications of autonomous vehicle insurance pricing in Germany, focusing on risk distribution, AI-based assessment frameworks, and emerging insurance models. The analysis highlights key risk factors, including cybersecurity threats, AI decision-making reliability, and V2V/V2I communication effectiveness, which influence insurance premium adjustments and liability allocation. The study further explores existing insurance frameworks and their limitations, emphasizing the need for new actuarial models that integrate real-time vehicle data, machine learning, and telematics-based risk assessment. Regulatory challenges are discussed in the context of EU and German liability laws, underscoring the ethical and legal complexities of AI-driven accident claims and responsibility sharing between manufacturers, AI developers, and insurers. The findings suggest that usage-based insurance (UBI), fleet policies, and blockchain-driven liability tracking will define the future of autonomous vehicle insurance. As AV adoption increases, insurers must adapt to data-driven, predictive, and scalable pricing models that ensure fair risk distribution and regulatory compliance while fostering public trust in self-driving mobility solutions.