Mehrabanpour, Mohammadreza, botshekan, mohammad hashem, Dana, Mohammad Mehdi. (1404). Identifying the drivers of assets quality review in Iranian banks. سامانه مدیریت نشریات علمی, (), -. doi: 10.22067/ijaaf.2025.95453.1589
Mohammadreza Mehrabanpour; mohammad hashem botshekan; Mohammad Mehdi Dana. "Identifying the drivers of assets quality review in Iranian banks". سامانه مدیریت نشریات علمی, , , 1404, -. doi: 10.22067/ijaaf.2025.95453.1589
Mehrabanpour, Mohammadreza, botshekan, mohammad hashem, Dana, Mohammad Mehdi. (1404). 'Identifying the drivers of assets quality review in Iranian banks', سامانه مدیریت نشریات علمی, (), pp. -. doi: 10.22067/ijaaf.2025.95453.1589
Mehrabanpour, Mohammadreza, botshekan, mohammad hashem, Dana, Mohammad Mehdi. Identifying the drivers of assets quality review in Iranian banks. سامانه مدیریت نشریات علمی, 1404; (): -. doi: 10.22067/ijaaf.2025.95453.1589
Identifying the drivers of assets quality review in Iranian banks
Iranian Journal of Accounting, Auditing and Finance
1Department of Accounting and Finance, Faculty of management and accounting, University of Tehran, Farabi Campus, Qom, Iran
2Associate Prof, Department of Finance and Banking, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.
3Ph.D in Accounting, Department of Accounting, Faculty of Business and Economics, Persian Gulf University, Bushehr, Iran.
چکیده
This study explores a critical issue in the Iranian banking industry, namely the review of asset quality. Previous studies show that a comprehensive model of asset quality review is still lacking. Only a few papers have systematically examined the factors affecting banks’ asset quality. Therefore, the main objective of this research is to identify and determine the key strategic drivers of Asset Quality Review (AQR) in Iranian banks. The methodology included a review of the theoretical literature, identification of variables through interviews with banking experts, screening of indicators using the fuzzy Delphi method with input from 37 experts, and analysis of interrelationships among variables with MICMAC software. Findings reveal that the determinants of AQR fall into five categories: financial, credit, supervisory, macroeconomic, and institutional. In total, 53 sub-indicators were validated. Results show that capital adequacy ratio, cost-to-income ratio, loan growth, non-performing loans, Collateral Valuation (CV) and compliance, inflation and interest rates, as well as legal requirements and auditing, are the most significant strategic drivers in this domain.