Presentation of the structural model of risk types in banks using the Fuzzy Interpretative Structural Modeling Approach

The experiences of recent decades in financial markets, and in particular the banks of different countries, indicate an increase in the importance of risk management in financial activities. Therefore, international efforts are aimed at creating a framework for standards that can be achieved by improving the financial health of the institution, especially banks. The axis of these standards has been manifested in creating an integrated risk management framework in the context of corporate risk management. The main purpose of the present research is to design a structural model of the types of existing risks in the banking sector. By studying thematic literature and using the textual content analysis approach, eleven effective risks were identified and for localization of them in the country's banking sector, Delphi technique was used for three periods of use It turned out The statistical population of the study consisted of managers and experts familiar with the subject and working in the banking sector. A researcher-made questionnaire was used to collect data. The reliability and validity of the questionnaire was confirmed by calculating Kendall's correlation coefficient (0.82) and Goghos and Boucher's correlation coefficient (0.08, 0.06), respectively. In order to design a structural model of risk, an interpretive structural modeling approach was used in fuzzy environment to manage linguistic ambiguity in judgments. The results of the Mick-Mac modeling and analysis showed that liquidity, credit, operational, interest rate, exchange rate risk and risk of laws and regulations are key and basic risks in the banking sector.