Design and Validation of a Financial Distress Risk Assessment Model Based on Interpretive Structural Modeling
Keywords:
Financial distress, Interpretive Structural Modeling (ISM), liquidity riskAbstract
This study examines the hierarchical structure of risks influencing the financial distress of banks using the Interpretive Structural Modeling (ISM) method. Financial distress, regarded as the stage preceding bankruptcy, arises from the complex interaction of internal and external factors affecting banks and has far-reaching implications for financial stability and economic growth. In this regard, key risk components—including liquidity risk, credit risk, market risk, and operational risk—were first identified, and their interrelationships were analyzed using ISM. The research findings revealed that the ratio of net profit to total bank assets and the ratio of net working capital to total bank assets, with impact coefficients of 99% and 94%, respectively, play the most significant roles in reducing the financial distress risk of listed banks. Furthermore, market risk, the market-to-book value ratio, and the total debt-to-total assets ratio, each with an impact coefficient of 91%, showed a similar effect in mitigating this risk. Other variables, such as operational risk, interest rate risk, net profit to equity, and total asset size, also demonstrated approximately 80% influence and ranked in subsequent positions. The power–dependence analysis showed that liquidity risk, with 100% driving power and 17% dependence, is positioned in the independent zone, whereas credit risk and operational risk, characterized by high driving power and medium dependence, are situated in the linkage zone. Variables such as net profit, working capital, and market risk, with 100% dependence but low driving power, are placed in the dependent zone.
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Copyright (c) 2025 Hadi Esmaili (Author); Hossein Jabbari; Davood Kianoosh , Hassan Ghodrati , Meysam Arabzadeh (Author)
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