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Technology innovation affects both the public and private non-financial sectors, the zakat institution (Islamic social finance) included. The institution uses an online system to communicate with zakat payers and zakat recipients to ensure its effectiveness in terms of collection and distribution. This research focuses on the adoption of a technique known as AD/AC and ZP/ZR, which is mainly utilized by partially and non-privatized State zakat institutions in Malaysia. To this end, three (3) techniques pertaining to appraising the performance of Malaysia’s Zakat institutions in managing Zakat funds were established. The analysis also includes the adverse impact of Covid-19 pandemic on the performance of zakat collection of the respective zakat institutions in Malaysia. In this relation, a quantitative approach was adopted using the primary and secondary data collected from JAWHAR and various states’ zakat institutions. By utilizing a technique of online data collection and applying the AD/AC as well as ZP/ZR methods, the performance of Malaysia’s zakat institutions is appraised. Furthermore, with the help two (2) ratios and eight (8) scenarios the performance of the innovative technique of AD/AC and ZP/ZR for zakat collection and disbursement, efficiency and sustainability of zakat institutions in Malaysia were evaluated. The results show that most zakat institutions, particularly those that deal with zakat payments, have begun to use the technique AD/AC and ZP/ZR within their organizations. The performance of zakat institutions in all states in terms of zakat distribution and disbursement do not have a consistent trend for the period 2016-2020. However, there is still a dearth of technology being used for zakat disbursements and fund reporting. From the observed data, with 2016 being the exception, for each remaining year, a state in Malaysia is ranked as the best technology performer or the most efficient. Selangor - fully privatized state (2017), Pulau Pinang - fully privatized state (2018), Federal Territory - partially privatized state (2019) and Negeri Sembilan-partially privatized state (2020) are the most efficient for the respective year. The sustainability of each zakat institution in Malaysia in the presence of Covid-19 pandemic was ascertained as well. Interestingly, contrary to the efficiency result, all non-privatized states (Kedah, Sabah and Kelantan) and one partially privatized state (Negeri Sembilan) were sustainable in coping with Covid-19 pandemic, while all fully privatized states (Selangor and Pulau Pinang) were not. Overall, it was conjectured that the technique AD/AC as well as ZP/ZR would help to improve the operations of zakat institutions to become more efficient and successful in distributing zakat fund to the poor. However, as zakat collecting and distribution involved millions of records, its management is still debatable by all parties.

Banks play an important role in the growth and development of any economy. A profitable banking system enhances economic stability and efficiency to mitigate the impacts of sudden macroeconomic shocks. To be more efficient and profitable, banks need to recognize the factors underpinning their performance. Accrued liabilities are one of the factors that hinder the profitability of banks. There are several methods to assess banks' profitability with their own pros and cons. Among them, data envelopment analysis (DEA) has been recommended as one of the most common approaches to evaluate different efficiencies including cost efficiency, revenue efficiency, technical efficiency, and finally profitability. The availability of prices/weights of inputs and outputs provides financial managers with significant information for evaluating efficiencies and assists them in decision-making and strategy development processes. This study mainly aims to analyze banks' profitability by considering accrued liabilities resulting from undesirable factors, for which relevant data were collected from 33 branches of a commercial bank in Gilan province, Iran based on managerial and weak disposability. The results illustrated that only three branches were graded one in three dimensions of efficiency, namely technical, cost and revenue, and profitability. Besides, it was suggested that the lack of these efficiencies was not correlated with the branches' profitability.

Objective: A study of the movement of the insurance industry returns shows that the movement of income returns was less than the movement of the insurance industry. The movements of lower income returns than the movements of paid losses of the insurance industry in the economy are due to various variables, including the management of the insurance industry, part of which is due to risk recognition. Which helps managers in the insurance industry, to the extent of tolerable and intolerable risks in the acceptance or non-acceptance of various swimming risks, and by managing them play an important role in marketing and increasing the demand for insurance and in general, In line with the optimal growth of the insurance industry. Methodology: This study, using generalized conditional autoregression models, ARIMA-GARCH / TARCH and beta coefficient, has evaluated the impact of risk on the return of the insurance industry in the Iranian economy during the period 1350-1398. Results: The results showed that there is a significant relationship between the study of the impact of risk on the return of Basma industry. Also in this research, systematic risk has been investigated using the beta coefficient method. Since the result of the impact of risk on the return on income of the insurance industry is 67%. Because the obtained beta coefficient is less than one and greater than zero. This result indicates that the income of the insurance industry is smaller than the general trend of market movement and risk aversion

The main purpose of this study is to determine the real and dynamic relationship between returns and stock market fluctuations in different time horizons so that its key results can measure the predictive power of returns and stock market fluctuations in determining the level of economic activity of investors. Accurate measurement of these relationships helps investors predict stock market movements in the future and Develop, plan and implement their own investment strategies in each time horizon. In this research Maximal overlap discrete wavelet transform has been used to investigate the relationships between industries return fluctuations and stock main indices in different time horizons from 2011 to 2020 have been estimated. The results showed that the wavelet variance of the rate of return varies in different industries. The return of investment companies on various time scales is equal to the investment return of the banking industry. The variance of the total index is less on different time scales than the value of the cash index.

The issue of asset pricing in the market is one of the most important and old issues in the financial world. Factor pricing models seek to be able to determine a significant relationship between return on assets based on the risk parameters of that asset. A wide range of factors can be found in the literature that can be an element for measuring the risk of an asset, but the big question is which of these models will work better. The factors studied in this research include factors that cover market risk, valuation risk, psychological (technical) market risk, profit quality risk, profitability, investment, etc. In this study, we have tried to Using machine learning techniques and optimization tools is a way to derive adaptive-robust nonlinear models that can reduce the risk of model error as much as possible. In this research, two models have been developed. In the first model, using the feature extraction technique and optimization of models based on neural network, a non-linear and adaptable model has been developed for each asset. In the second approach, a portfolio of improved neural network-based models is used in the first stage, which can be used to minimize the risk of model error and achieve a model that is resistant to different market conditions. Finally, it can be seen that the development of these models can significantly improve the risk of error and average error of the model compared to traditional CAPM approaches and the Fama and French three-factor model.