Presenting a risky investment model in the insurance industry based on the fuzzy network analysis process

The purpose of this paper is to identify and present a high-risk investment model for insurance institutions in order to establish a risky insurance investment fund. In this paper, it has been tried to identify and introduce the most important factors and effective factors of venture capital (VC) using the technique of fuzzy network analysis process in the insurance industry. The data needed for the research has been collected through in-depth interviews with a number of experts and researchers in the insurance industry, as well as a questionnaire. Due to the lack of independence and the existence of dependence between the effective factors, the method of fuzzy network analysis process was used to identify the possible dependencies between factors and measure them for the development of the VC model, and the results were prioritized with the method of non-fuzzy network analysis process. Is. The findings of the research show that operating cycle indicators, total asset turnover ratio, total investment return, loss factor, asset-liability ratio are ranked first to fifth among VC indicators. VCs help the insurance industry establish internal accounting rules and standardize their financial statements. In other words, VC support modifies the "hard" and "soft" information required for insurance.