Interactive scenario analysis of banking credit risks in intuitive fuzzy space

Purpose: The purpose of the paper is to bring attention to documentary credits and the efforts to reduce debt obligations in credit history is recognized as an important source of uncommitted bank earnings. Credit risk has a significant impact on the stability of the banking system. This paper identifies the types of credit risk in the banking supply chain. Design/methodology/approach: The authors model the types of credit risk using the intuitive fuzzy failure modes and effects analysis (IFMEA) and intuitive fuzzy cognitive mapping. The population of the study that is needed for the interviews and expert panels comprises senior managers and experts of a leading bank in Iran. The respondents are experienced in credit and banking risk and were selected through judgment sampling and snowballing. Findings: The findings suggest that reducing the risks of the foreign letters of credit contracts can mitigate the risk in the agricultural sector, the specific risks of rent-to-own contracts, the risk of the long-term facilities and the specific risk of the domestic letter of credit contracts. Originality/value: This research investigates Iran Tejart Bank’s credit risk, formulates a model of the types of credit risk present and analyzes them using the intuitive fuzzy failure modes and effects analysis and intuitive fuzzy cognitive map. Through this credit risk model, one can then facilitate risk management for better financial stability. Also, the model can be used to evaluate the risk indicators.