Providing a Risky Investment Model in the Insurance Industry based on the Fuzzy Network Analysis Process

Identifying and presenting a high-risk investment model for insurance institutions in line with the establishment of an insurance risk-taking investment fund. This research is considered to be applied in terms of purpose and field descriptive in terms of nature, and because it tries to present a model using the process of fuzzy network analysis, it is also considered as a type of modelling. In this paper, it has been tried to identify and introduce the most important factors and effective factors of venture capital (VC) using the fuzzy network analysis process technique in the insurance industry. The population of this study was insurance companies and the statistical sample includes ۵۴ experts in the field of insurance. The required information was collected in ۲۰۲۳ using a standard questionnaire. Due to the lack of independence and dependence between the effective factors, the fuzzy network analysis process method was used to identify the possible dependencies between the factors and measure them for the development of the VC model, and the results were prioritized by the non-fuzzy network analysis process method. The findings of the research show that operating cycle indicators, total asset turnover ratio, total investment return, loss ratio, asset-to-debt ratio are ranked first to fifth among VC indicators. Venture capital helps the insurance industry to establish internal accounting rules and standardize their financial statements. In other words, venture capital support modifies the "hard" and "soft" information required for insurance.