فصلنامه پژوهش های پولی - بانکی
پیاپی 55 (بهار 1402)

The fight against financial corruption is divided into two parts: preventive campaigns and post-combat campaigns. Most of the countries that have been successful in the fight against corruption have used preventive fighting methods. One of the methods of preventive campaigns is to identify and strengthen the factors that prevent financial corruption in any system. Due to the high volume of monetary and financial exchanges and its business nature, the country's banking system can deal with the most sinister phenomenon (financial corruption). The country's banking system, like all other organizations, foresees and implements various laws, organizations, factors and structures in order to prevent and fight financial corruption, according to their working conditions. In this research, by using the Delphi method, existing factors that prevent financial corruption in the country's banking system will be identified, and then by implementing Friedman's test, prioritization and weighting and the degree of influence of each factor will be done. After conducting the research, 6 main factors (criteria) and 24 secondary factors (sub-criteria) were identified. The ranking of the factors preventing financial corruption are in the order of economic, structural, political, managerial, individual, and social factors.

Intellectual capital is the effort to effectively use knowledge as a final product against information as a raw material, and it is one of the vital resources to develop the productivity and performance of banks. According to the view based on intellectual capital and the resource-based view, intellectual capitals are the only strategic resources that enable the organization to create value and as a result create a superior and sustainable competitive advantage. The purpose of this research is to examine the relationship between intellectual capital, bank stability and risk-taking in accepted banks listed in the Tehran Stock Exchange. The sample size includes 12 banks, which have been studied to investigate the hypothesis of the 7-year information research of these banks during the years (1394-1400). Eviews software has been used to review and analyze the data of this research. The findings of the research show that there is a significant relationship between intellectual capital and the stability of banks in the banks admitted to the Tehran Stock Exchange. Also, there is a significant relationship between intellectual capital and risk-taking in banks admitted to the Tehran Stock Exchange. These results can help banks in designing and using targeted policies about banks' intellectual capital, which increases the stability of banks.

In this study the usefulness of fair value compared with cost of loans for predicting non-performing loans is tested. Also, in line with stabilization and completion of research findings, expected credit loss compared with loss impairment and reserve of loss impairment of loans for predicting banks, future operational profitability is tested. The hypotheses of the study were tested by static and dynamic panel through the panel data gathered from 14 listed banks in Tehran Stock Exchange during 2014- 2021. The findings of the first hypothesis of the research indicated that only the fair value of loans has ability to predict non-performing loans of banks. The findings of the second hypothesis of the research indicated that the expected credit loss compared with retained loss impairment of loans, has more ability to predict one year-future operational profitability of banks. The findings of the third hypothesis of the research indicated that only expected credit loss has ability to predict two year-future operational profitability of banks.

Asset and Liability Management (ALM) is one of the most important tools that senior executives of a bank, including the CEO and the board of directors, should consider in monitoring and controlling the financial health and enhancing the financial capability of the bank. This article presents a mathematical optimization model based on Goal programming (GP), with an emphasis on the most crucial pillar of optimizing the operational allocation of the balance sheet structure in banks. The considered constraints in the model take into account the importance of regulatory laws and regulations approved by the Monetary and Credit Council and communicated by the Central Bank to the banking network within the key constraints of linear programming in the model. The results obtained from this article emphasize that liquidity Goal constraint and regulatory Goal constraint have a significant and effective impact on improving the balance sheet management structure of banks and reducing liquidity risk.

One of the main functions of banks is maturity transformation as borrowing in the form of deposit in the short term and lending long term. The role of banks in financing and investment needs of businesses is obvious. Bank lending to applicants through the effective action takes place. In this regard, having adequate and sufficient capital is critical to keeping up the health of the banking system. In the meantime, as the most important international agreement in order to ensure banking health the rules of the Basel committee's agreements have paid special attention to the observance of the minimum capital adequacy. Considering the importance of this issue and since banks are one of the most important providers of financial resources in Iran, In this study, by using the financial ratios and characteristics of the balance sheet structure of 25 banks active in the country's banking system, in the period of 1385 to 1398, capital adequacy deviation index was proposed. In the following, the effect of the suggested capital adequacy deviation  index as an independent variable along with other banking and macroeconomic variables on the bank lending by the method of generalized moments (GMM) are discussed. Accordingly, the results show that the effect of the capital adequacy deviation index on the lending is confirmed, and the index has a significant and inverse relation on the bank lending. The research findings also indicate that the effect of bank size on banks' lending is confirmed, and bank size has a significant and direct effect on bank lending. Based on the results, the simultaneous effect of bank size and capital adequacy deviation index on the lending was also confirmed. In other words, the simultaneous effect of these two variables on the bank lending is inverse and significant.

Banks and credit institutions through attracting financial sources in the form of bank deposits and allocation them in the form of variety of loans, play an important and vital role in the economy of any country. Banking activities, due to Special features such as, high leverage degrees, existence of maturity mismatch between assets and liabilities, contagion the problems to other institutions, and the last but not least, having direct impact on Macroeconomic conditions, necessarily requires risk acceptance, which depends on the dimension, complexity of activity and degrees of systematically important and in the lack of effective supervision, can affect both economy and financial systems, domestically and even internationally. Systemic risk is the probability of sudden fall in total financial system and can lead to instability or chaos in financial markets. The systematically important institution is an entity that in the event of a crisis due to its special characteristics such as, size, market share, interconnectedness, cross boarder activities, complexity and etc. can have important effects on domestic or even international macroeconomic condition. So, the importance of Convergence in the field of managing banks and existent of homogenous rules and regulation in this very important industry is completely obvious. Considering that no study and research has been done about systematically important banks in Iran, the main goal of this research is to develop the methodology to determine systematically important banks in Iranian banking system and then measuring Systemic risk using ΔCoVaR and MES. The time period under review is from the beginning of 2014 to June 21, 2022. The results show that there are many qualitative similarities between the systemic risk calculated by theΔCoVaR and MES, despite the numerical differences. Also, according to the results of both methods, Tejarat, Parsian, Pasargad, Saderat, Novin Eghtesad and Mellat had the highest to lowest level of systemic risk in the study period respectively.