Quarterly Studies in Banking Management and Islamic Banking

Abstract This article is a systematic review of the literature of 59 empirical studies published during the period of 1979-2024, which investigated the factors affecting the profitability of banks. Therefore, it pursues a dual purpose. On the one hand, any decision making by bank management needs to consider the factors which affect their profitability. On the other hand, access to research methods related to factor affecting bank profitability gives researchers the possibility of practical and at the same time more complex research. In order to investigate the factors affecting the profitability of banks, the innovative method of analyzing the concept-oriented matrix was used. Based on this method, the three general dimensions of factors affecting bank profitability, i.e., cyclical, structural, and specific factors of banks, were combined, and next, using the open coding process, the relevant literature was carefully analyzed in 17 sub-categories. The results of the present study show that the interaction of cyclical, structural, and specific factors of banks on their profitability still lacks deep understanding and needs more empirical research. Also, the holistic approach offers a new style of examining existing research and highlights the gap between what we know and what we need to know.

Abstract The issue of intellectual capital and its use as one of the main sources of competitive advantage has been investigated in numerous studies, and human capital and structural capital have always been regarded as two important components in many studies. Considering the importance of intellectual capital, the present study explores the effect of human and structural capital on the profitability and management of Iranian commercial banks using the quantile regression method. The data taken from the audited financial statements of 12 banks for 11 years were used in this study and the results show the significant effects of human capital in different quantiles on the profitability and management of such banks, while the impact of structural capital is only in one quantile. Also, the shape of the function was examined according to the literature and the results show a U-shaped relationship between human capital on the one hand and profitability and management on the other hand.

Abstract The global financial crises brought traditional reporting under many criticisms, mainly due to the lack of disclosure of sufficient information in this reporting system. With the advancement of technology and emerging needs of society, managers and stakeholders have realized the importance of non-financial reporting. Integrated reporting through the inclusion of both financial and non-financial information (environmental, social, managerial, economic, etc.) in a single document improves the quality of reporting and defines the organization's prospects for value creation. The purpose of the present article is to identify integrated reporting indicators in Iran's banking industry. In this regard, after studying the literature and the background of integrated reporting, the annual report of 27 foreign banks (issued in 2022) was studied and then through the content analysis of interview scripts with experts, the initial framework including 8 main components and 47 general indicators was compiled. Next, using a questionnaire, the fuzzy Delphi method and the Fuzzy Analytical Hierarchy (FAHP) method, the general indicators were confirmed and ranked. The results of using the extracted components and indicators, as well as the opinion of banking experts and the review of laws and regulations, indicated that the final integrated reporting framework for the banking industry of Iran includes 8 components, 47 general indicators, and 172 partial indicators. This framework can be used by legislative and supervisory institutions to develop reporting standards and requirements. Also, banks can use it in order to clarify and disclose information beyond the requirements.

Abstract Money laundering is one of the most fundamental issues in Iran's economic system and banks. Money laundering can have very destructive effects on a country’s economy and society; Therefore, legal and executive solutions with high effectiveness are important to deal with it. International organizations and institutions active in the field of combating money laundering, such as the Financial Action Task Force (FATF), continuously examine and evaluate countries and organizations and classify them based on the calculated risk level. In countries that are in the high-risk category banking transactions face major challenges and economic and financial activities tend to be difficult. Based on this, the importance of combating money laundering and compliance with international standards increases. With regard to the very high volume of data generated from various face-to-face and non-face-to-face channels in the banking industry, it is necessary to apply proper governance to them in order to fight money laundering. Technological solutions, artificial intelligence, machine learning and a risk-based approach to deal with money laundering go through the path of access to high-quality data. According to the research questions, Bank Mellat, one of the largest commercial banks in Iran, was selected for the statistical population and in order to identify the data governance framework in the fight against money laundering through targeted and snowball sampling, 14 managers and expert experts with the highest scores were selected for interviews. 750 people were included. By conducting an in-depth interview and using the foundation's data theorizing method, a paradigm model of the data governance framework was designed from 43 extracted codes in the form of 18 concepts and 6 categories. Subsequently, the designed model was given to academic and experimental experts and evaluated. The study findings are explained and the results and future suggestions are presented.

Abstract Compliance with the capital adequacy requirements provided by the Basel Committee on Banking Supervisions is one of the most vital needs of banking in Iran. In this regard, this article reviews the methods for estimating the loss given default (LGD) as one of the two main variables in determining the credit risk of a debt. This variable is used in various areas of credit risk management, including loan pricing, loss reserve determination, credit rating, and determining capital adequacy. Therefore, in this study, while reviewing the methods of estimating this variable in the various approaches in Basel accords including “fundamental internal rating” and “advanced internal rating,” the common practice that is currently used to implement the advanced internal rating approach to estimate loss given default is described in details. Also, reviewing several important studies in the field, the estimation methods used in these studies, and the results of using different statistical methods in modeling loss given default have been presented.

Abstract Banks are the most important financial market institutions in the country that can play an effective role in economic development. The main purpose of this study is to estimate the efficiency, effectiveness, and productivity of Sepah Bank branches, located in Tabriz, Iran, using the method of Network Data Envelopment Analysis (NDEA). Another purpose is to investigate the financial imbalance of these branches using the ordinary least squares method. The results of this study indicate that the most efficient branches or the most effective branches are not necessarily in good conditions in terms of productivity. In other words, the efficiency of branches does not necessarily mean their productivity, whereas the most productive bank branches definitely operate at a high level of efficiency and effectiveness. On the other hand, an inverse relationship is revealed to exist between these branches' income-cost imbalance and their productivity.