Distribution Channel Models in Life Insurance: Identifying Key Influencing Factors

The life insurance industry is undergoing significant transformation driven by evolving consumer preferences, technological advancements and changing market dynamics. As insurers adapt to a changing landscape, distribution channel models are becoming a critically important factor in determining success and profitability in the market. The aim of this article is to develop a scientific and methodological basis for substantiating distribution models for life insurance products, which involves defining homogeneous groups of countries and identifying key factors that influence sales models. The methodological tools used in this study were Gaussian mixture models to determine the distribution models of life insurance products and the common factor rotation method (Varimax) to calculate the degree of influence of relevant indicators on the distribution models. The research period is 2008--2019, and the objects of the study are 13 countries in the European Union. Calculations are performed via the Python programming language. This article presents the results of a cluster analysis of countries, which allowed us to identify three key models in the sale of life insurance products: the bancassurance model (Spain, France, Italy, Malta, Portugal), the intermediary model (Bulgaria, Germany, Hungary) and the hybrid model (Sweden and the United Kingdom). Analysis of changes in cluster distribution indicates stability in the grouping of most countries, although in some cases, there is a transition between clusters. By identifying similarities and differences between countries and analysing the impact of socioeconomic and technological factors, this study contributes to the development of effective distribution strategies in the dynamic insurance market. The results of factor analysis revealed that the most significant differences between clusters were observed in indicators of internet access, level of education and index of hours worked. The greatest impact on the bancassurance product distribution model is exerted by digital development indicators (frequency of internet use, level of internet access), the intermediary model, the level of citizens’ access to the internet and the level of citizens’ education, and the hybrid model, the frequency of internet use and the level of urbanization in the country. The results of this study have practical importance for insurance companies and financial institutions seeking to optimize their distribution channels and adapt to modern market requirements.