Exploring the Impacts of Autonomous Vehicles on the Insurance Industry and Strategies for Adaptation

This study investigates the impacts of autonomous vehicles (AVs) on the insurance industry from the viewpoint of insurance companies, highlighting the necessity for adaptation due to technological advancements. The research is motivated by the gap in understanding between traditional insurers and automaker-backed insurance services regarding AV implications. The purpose is to identify potential impacts, evaluate the level of concern among diverse insurance companies, and examine their differing perspectives. The methodology includes a literature review, the Analytic Hierarchy Process (AHP), and Spearman correlation analysis. The literature review clarifies the definition of AVs and their impacts on traditional insurance. The AHP assesses the level of concern among insurance companies, and Spearman correlation analysis explores the similarities and differences in perspectives. The findings show that insurance companies largely agree on the transformative impacts of AVs. The primary effects are in “Updates in Insurance Business Operations” and the “Emergence of New Risks”, with less impact on “Changes in the Insurance Market”. A major concern is the complexity of multi-party liability claims. Companies differ in their focus on specific impacts like legal frameworks or system malfunctions, but share concerns about multi-party liability, system malfunctions, and legal gaps. The study anticipates minor impacts on market dynamics and traditional insurance models. The conclusions emphasize that AVs will significantly impact the insurance industry, requiring innovation and adaptation to maintain competitiveness. This includes developing new products, optimizing processes, and collaborating with stakeholders. The study has several implications: customized insurance products, optimized no-fault claims processes, collaborations with automakers and tech firms, data-driven risk assessments, enhanced risk management, and adapting traditional models. Recommendations include building loss experience databases, adopting no-fault insurance, strategic partnerships, developing customized products, strengthening risk management and cybersecurity, monitoring regulations, adjusting traditional models, focusing on product liability insurance, and training professionals.