Exploring the Synergy of AI and Blockchain in Insurance: A Bibliometric Mapping and Analysis of Research Trends

Abstract

Integrating artificial intelligence (AI) with blockchain in the insurance industry has transformed risk assessment, streamlined claims processing, and enhanced data security, resulting in more efficient and transparent operations. This study conducts a bibliometric analysis to examine the scholarly landscape on AI and blockchain applications in insurance, using Biblioshiny and VOSviewer software to analyze data from the Scopus database. Key metrics explored include Annual Scientific Production, Most Significant Authors, and Most Relevant Sources, shedding light on influential contributors and foundational publications. Additionally, we examined the Most Globally Cited Documents and Trend Topics to trace the evolution of research interest over time. Clustering methods such as Clustering by Coupling and Thematic Mapping provided insights into the structural composition of the field. By assessing the Co-occurrence of Keywords and the Citation Network of Authors, the analysis highlights prominent topics and collaborative patterns. The Co-Authorship by Country metric further reveals international partnerships in advancing AI and blockchain research for insurance. Through this study, several research gaps were identified, such as the need for deeper exploration of human-centered insurance applications and blockchain-based peer-to-peer models. These findings offer valuable insights for researchers and practitioners, guiding future studies and innovations in the field..