Anticipation of Financial Crisis in Banks by Structural Equations Model

Undeniable effects of banking crisis on economy and need for anticipating the crisis before occurrence, remind necessity of existence of a model for anticipating the banking crisis. The aim of this study is to provide a complete model that includes all of the effective variables on the banking crisis, so we can help better anticipation of banking crisis. For doing this research, the literature was studied and variables that cause banking crisis was identified. Next, research data for 21 banks from 2013 to 2022 was gathered and analyized. The research model was developed by structural equations modeling method. Finally for measuring the models precision, artificial neural networks was employed. The result of the research shows that financial variables, Internal non-financial variables, banking sector variables and macroeconomic variables cause bank distress and most important factors in bank distress anticipation are: human resource, corporate governance, liquidity and capital adequacy. Also, this model could distinguish between distressed bank and healthy one in both train and test groups with precision of 100 percent. With introducing the important factors causing the banking distress, this model can provide a buffer for bank managers and central bank for doing the preventive and corrective actions.