Operational risk along with its management methods is considered as one of the significant fields in banking industry, which has potential influences on the performance of banking and financial institutes.One of the major steps in managing Operational risk is its measurement which is aimed at measuring the required capital for this risk.Regarding the fact that banks have been trying to observe regulations and standards of Basel Committee more than before, measuring the required capital for Operational risk to confront the crises and to place it in capital adequacy ratio is of great significance.There are three approaches to measure Operational risk capital, such as the basic indicator approach, the standardized approach and the advanced measurement approach. In comparison with the advanced measurement approach, the two approaches of the basic and standardized require less data. That is because the former one needs a wide range of loss data.

The aim of this paper is to investigate the relationship between conservative risk management and operating cash flow in accepted companies in Tehran Stock Exchange. The research method was descriptive-correlation and hypotheses have been tested by using regression models and panel data methods.122 companies were involved as the research sample. Library method using book, thesis, and Persian and Latin papers has been used to collect literature. For collecting statistical data the financial statements of accepted companies of Tehran Stock Exchange was used. The results of the analysis at 95% confidence level indicate that there's a significant relationship between conservatism and operating cash flow. There's all so a positive and significant relationship between unconditioned conservatism and operating cash flow. But there's no relationship between operating cash flow and conservatism.

Industrial operations in high H2S gas wells can cause serious environmental, financial & health consequences. risk management is important, especially when the world is at war with the SARS-COV-2 pandemic; we should have stronger boundaries to protect lives. One of the common methods is the hierarchy method. In this study, by combining this method and designing a new correlation to calculate static bottom hole pressure at gas wells, we tried to have strong risk management with the final goal of replacing the industrial operation. In the past, time-consuming and imprecise trial and error methods& expensive operations were used to calculate static bottom-hole pressure for gas wells. So, a general equation was modified based on field observations to obtain more accurate static bottom-hole pressure predictions. For this purpose, a unique adjustable parameter, based on the history matching of wells, has been proposed for each reservoir. The accuracy of this equation was investigated in three Iranian gas reservoir information. Good agreement was obtained between the field observations and this proposed equation. The precision of this method depends on field data, and with increasing numbers of field tests, the model becomes more accurate.

In recent years, after the economic crises, the value of Operational risk assessment has been observed in the financial industry, while the biggest impact of Operational risk has been on the banking industry. As a result, more attention has been paid to Operational risk assessment in the banking industry after the financial crisis. Operational risk is defined as the risk of loss caused by the inadequacy or inefficiency of internal processes, people, systems, or external events. In this regard, institutions and banks have been looking for Operational risk assessment by taking different approaches, including the approaches of the Basel Committee. The current research aimed to review Operational risk management in the banking industry. Using the meta-synthesis method, 643 related research documents between 2000 and 2022 were gathered from among reliable scientific databases. By using this method, 43 final documents made the basis for extracting the findings. Finally, this method identified 5 main categories, including Operational risk, risk assessment, risk quantification methods, risk analysis, and risk management, as well as 10 subcategories consisting of 43 concepts and 169 codes. The results were confirmed based on the experts’ opinions with a kappa index of 0.756.Keywords: Operational risk, Advanced Measurement Approach, Basic Index Approach, Standard Approach, risk management. IntroductionThe significant losses suffered by financial and non-financial institutions from various non-credit and non-market processes and factors have made many managers and decision-makers of these organizations pay attention to the field of "Operational risk". Operational risk and its management methods are significant topics in the banking industry. They have potential effects on the performance of banks and financial institutions. According to the conducted research, authors have looked at risk from different perspectives. The relevant groups have focused on the definition of risk, classification of Operational risk events, measurement and characteristics of Operational risk management, and comparative analysis of different estimates (Barakat & Hussainey, 2013). Method and DataThe current study was an applied research based on collecting documentary information. Using the meta-combination method, 643 related research documents between 2000 and 2022 were gathered from reliable scientific databases. By using this method, 43 documents finally made the basis for extracting the findings. FindingsUsing the meta-synthesis method, 643 related research documents between 2000 and 2022 were gathered from reliable scientific databases. By using this method, 43 documents made the basis for extracting the findings. Finally, this method identified 5 main categories, including Operational risk, risk assessment, risk quantification methods, risk analysis, and risk management, as well as 10 subcategories, 43 concepts, and 169 codes. The results were confirmed based on the experts’ opinions with a kappa index of 0.756. Discussion of results & Conclusion In this research, the studies conducted in the field of Operational risk were classified by using the meta-synthesis method. The meta-synthesis method was consisted of 7 steps. First, the questions related to the research were designed. In the second stage of the systematic literature review, 643 related articles in the field of Operational risk from 2000 to 2022 were collected. In the next step, the related articles were selected based on title, abstract, and text. Then, 43 related articles were identified and 169 codes were extracted. Afterwards, the data analysis and data synthesis were done and the numbers of main categories, subcategories, and concepts were identified. In the sixth stage, quality control was performed and used to determine the value of Cronbach's alpha from the experts’ points of view. In the last stage, the relationships between the research findings were shown by using a tree diagram. In the field of Operational risk, the meta-synthesis method had not been used for systematic review, classification, and categorization of the results of the articles. In this research, unlike the previous research, the related articles were classified by using the meta-synthesis method. Then, the categories and concepts were extracted and the relationships between them were shown in the form of a tree diagram.

In accordance with Basel Committee definition, Operational risk is the exposure of inadequacy of the processes, people and internal systems or external events. Operational risk management is an ongoing process in the organization, although implementation of enterprise risk management depends on goal setting, planning and organizing. There are some barriers and obstacles against the efforts for Operational risk management that this research firstly wants to identify, then prioritize them using a qualitative method namely Delphi method and Friedman test as a Non-parametric method respectively. If risk managers find the main obstacles that prevent the implementation of Operational risk management, they could easily control them.

As every other business, there are a variety of risks in the banking industry, including Operational risks. The Central Bank of the Islamic Republic of Iran, as the Basel Committee, has required computing and managing the Operational risk for banks and financial institutions. Accordingly, the goal of this study is to evaluate the Operational risk management in banks based on the Basel II accord methodology. This study is of case study type. That is to achieve the research purpose, the Bank Hekmat Iranian (merged with Bank Sepah) was chosen as a young bank in Iran. Due to access to the bank's financial statements, no sampling was used and all audited statements of this bank over 2011 to 2016 were selected as the statistical population of the study. Then, the Operational risk of this bank was calculated using two "Basic Indicator" and "Standardized" approaches based on the Basel II accord methodology. Also, the Central Bank of the Islamic Republic of Iran directive were used to identify different groups of bank activity in Standardized method. Descriptive statistics were used for data analysis. The results represent an ascending slope in Operational risk in this bank over the research period. Due to the impact of the volume and the extent of banks' operations on the operating risk, this result could be due to an increase in the scope and volume of the operations in the bank during these years, which has directly affected the Operational risk. This paper, while providing a relatively comprehensive and coherent literature about the Operational risk, also provides details for calculating of this risk in banks. These details are based on the bank’s audited financial statements and can be used as a pattern to calculate Operational risk in other banks. Introduction Every economic activity is exposed to risk. Because economic activities deal with the future and the future is always faced with risk and uncertainty. Credit and financial institutions are no exception. These institutions face a variety of risks, including credit risk, market risk and Operational risk. Operational risk is the risk associated with the way a bank operates and manages its operations. Every risk arising from the way a bank operates is somehow indicative of Operational risk. Operational risk factors can be within the organization (eg management and staff performance) or outside the organization (eg natural disasters). The variety of factors that can lead to Operational risk has made it difficult to measure this risk. Each bank's management must identify mechanisms for identifying and managing the risk and mobilize organizational culture to control and mitigate this risk. As described above, it is essential that banks and financial institutions are actively involved in the risk management process in order to monitor, manage and measure Operational risk. They must have methods for quantifying Operational risk so that they can calculate and control and mitigate this risk in their management scope. Therefore, the main question in this study is how much a bank's Operational risk is according to the Basel II accord methodology. Case study This study is of case study type and the statistical population of the study is the data extracted from the audited financial statements of the Bank Hekmat Iranian (merged with Bank Sepah) during the research period. Since access to this data is feasible for the purpose of this study, sampling has not been used and the entire statistical population has been investigated. Materials and Methods Following Basel II (2006) and Central Bank of the Islamic Republic of Iran (2007) instructions, the “basic index” and the “standardized” approaches are used to calculate Operational risk. In the “basic index” approach, a bank's Operational risk per year equals a constant percentage of the bank's average earnings over the last three years. The “standardized” approach is similar to the “basic index” approach, except that it takes into account the fact that Operational risk can vary between different segments of banks' operations. The “standardized” approach divides the bank's activities into eight working groups and considers for each working group a separate percentage of the average gross income as the operating risk for that group. Descriptive statistics were used to analyze and interpret the results. Discussion and Results The results showed that although the amount of Operational risk in the “basic index” and the “standardized” approaches is slightly different and is greater in “standardized” approach than the “basic index” approach, but both methods show an increasing slope for the Operational risk since 2014 to 2017. This means that the operating risk for Bank Hekmat Iranian has increased over these years. Conclusion The results can be interpreted as having a significant increase in the volume and scope of operations of the Bank Hekmat Iranian (merged with Bank Sepah) from 2014 to 2017, the risk associated with these operations has been increased too. Since the scope of Operational risk is very wide and encompasses almost all aspects of bank activity, it is natural that as the scope of bank operations broadens, operating risk will increase. Of course, this increase is due to the expansion of the bank's operations and its upward trend and does not necessarily have a negative message for the bank. Because the higher the risk, the higher the return. Banks may rely on the output of the standardized approach to apply more stringent and maximum precautionary measures and consider larger precautionary reserves to cover the capital required for Operational risk.

In this paper we distinguish between Operational risks depending on whether the Operational risk naturally arises in the context of model risk. As the pricing model exposes itself to Operational errors whenever it updates and improves its invest-ment model and other related parameters. In this case, it is no longer optimal to implement the best model. Generally, an option is exercised in a jump-diffusion model, if the stock price either exactly hits the early exercise boundary or the price jumps into the exercise price region. However paths of the diffusion process are continuous. In this paper the impact of Operational risk on the option pricing through the implementation of Mitra’ s model with jump diffusion model is pre-sented. A partial integral differential equation is derived and the impact of param-eters of Merton’ s model on Operational risk and option value by Operational value at risk measure is employed. The option values in the presence of Operational risk on data set are computed and some of the results are presented.