Insurtech research dynamics: A bibliometric review of technological innovations in insurance

This bibliometric study on insurtech explores the transformative impact of technological innovations such as AI, machine learning, big data, IoT, and blockchain on the insurance industry. Utilizing Scopus for bibliographic data and adhering to the PRISMA flow chart for the meticulous screening, inclusion, and exclusion of studies, the research employs advanced bibliometric tools including biblioshiny, VOSviewer, and CiteSpace to conduct a comprehensive analysis. The findings reveal an upward trend in annual scientific production, highlighting the field's dynamic evolution and growing interest. The study identifies the most productive authors and analyzes coauthorship patterns to understand collaboration networks. Through cocitation analysis, influential authors and seminal works are identified, offering insights into the academic lineage and intellectual foundations of insurtech research. Network visualizations of citations, both of references and journals, alongside the co-occurrence of keywords, map out the thematic and disciplinary landscapes, pinpointing the most relevant sources and globally cited documents. The overlay network visualization of document citations further elucidates the thematic concentrations and evolutionary trajectories within the field. Additionally, this research identified key research gaps and outlined practical implications, pointing to areas that can be ripe for further exploration and innovation and can be helpful in practice. In the same way, the scientific production and collaboration country mappings draw a map of the global distribution and network of insurtech research and bring out more of its international scope and interdisciplinary nature. This bibliometric analysis does not just describe the current state of insurtech research but provides a strategic framework of how one may be able to orient themselves around future developments in this fast-evolving field.