Search Results for محمد Ibrahim

Abstract

The research addresses two main topics: the International Public Sector Standard (IPSAS 24) relating to the presentation of budget information in financial statements, and the Government Financial Management Information System (GFMIS).

In relation to IPSAS 24, the research focuses on clarifying how budget information is presented in public sector financial statements. The standard aims to achieve transparency and reliability in providing financial information to governments and government institutions. The research addresses various aspects of the standard, such as defining financial terms, basic principles, and requirements that must be met in submitting the budget.

 For GFMIS, the research reviews and evaluates this system that is used in managing financial information for governments. GFMIS aims to improve the efficiency and effectiveness of government financial resources management, and facilitate financial planning, monitoring and evaluation processes. The concept of GFMIS, its components and benefits are reviewed, as well as the challenges of its implementation and future preferences for its development and improvement.

 Overall, the research aims to provide previous researchers with an overview of IPSAS 24 and its importance in presenting budget information in public sector financial statements, as well as reviewing GFMIS and its role in improving government financial information management. This research can contribute to raising public sector awareness of the importance of adhering to international accounting standards in the public sector and using advanced financial information management systems to enhance transparency and effectiveness in managing the financial resources of governments.

The main reason for linking these two variables is to enhance transparency, accountability, and financial control in the public sector and ensure that government financial information complies with international accounting standards in the public sector. Therefore, reviewing these two variables and analyzing their role will provide an important theoretical and applied framework for understanding the relationship between them to rationalize the budget. The most important conclusions reached for the review research are that the main goal of applying the (IPSAS) standards is to achieve compatibility in accounting policies at the global level by providing guidance and directives to develop a comprehensive theoretical framework for government accounting. Evaluating government performance is achieved through commitment to applying the (24 IPSAS) standard., which allows the preparation of a variety of financial statements detailing the approved budget and actual expenditures, the final budget (adjusted allocation), and achieving the qualitative characteristics of accounting information. The government unit did not disclose in the financial statements the extent of compliance with legislative and regulatory laws and other regulations imposed by external parties. (The State) As for the recommendations, the researchers suggest that government institutions should commit to implementing the IPSAS 24 standard completely and accurately to ensure compliance with international accounting standards. Government institutions should analyze their actual needs and conduct a feasibility study before making any transfers in the original budget, in order to ensure a strong scientific basis and improve the institution’s performance in adhering to budget directives. Government institutions should fully and effectively implement GFMIS in all government units to enhance transparency and financial control. The GFMIS should also be configured in a way that meets the needs of the government unit in a way that enables it to record and track financial transactions and prepare financial reports in an accurate and timely manner.

Abstract

This research is about a statement of the event that information related to recidivism and its dimensions of (saving data, investing time, justice, justice, corruption, administrative corruption, discovering tax evasion, stimulating the media, the efficiency and completeness of information and the right time), and the descriptive analytical approach has been adopted.  In light of it, the questionnaire was designed as a tool for those responsible for collecting data for the study, based on the statistical program (SPSS V.18), and the search for a related relationship with statistical significance for housing information in support was found to remove the impact of the information of the supporting bodies collectively or individually in the tax inventory 

Abstract

Foreign trade is one of the basic sectors of any country's economy. It is of great importance in developing economic relations between countries worldwide, especially developed and developing countries, through the import and export of goods and services, both visible and invisible, and the movement of capital and gold trading. Foreign trade activities are usually carried out through the mechanism of linking the exchange rate of the local currency to foreign currencies. The importance of this study lies in highlighting the fluctuations in the exchange rate of the Iraqi dinar against a basket of foreign currencies, especially the US dollar. These fluctuations directly affect the economy in general and the costs of importing goods and services in particular. This study aims to measure and analyze the impact of exchange rate fluctuations on Iraqi imports for the period 2004–2023. To achieve the study objective, the study relied on time series data and used the Autoregressive Distributed Lag (ARDL) model to analyze the relationship between the dependent and explanatory variables in the long and short term. The study found a statistically significant positive relationship at the 5% level between the exchange rate and imports in the long term, which means that the rise in exchange rates in Iraq led to an increase in the volume of imports during the study period. based on these results, the study recommends the need to create a stable economic environment for the exchange rate of the Iraqi dinar against foreign currencies, especially the US dollar, in addition to strengthening the role of the Central Bank of Iraq in controlling the official and parallel exchange rates to limit their negative impact on the increase in consumer imports.

Abstract

This study aimed to examine the impact of applying the Blue Ocean Strategy on enhancing the competitive advantage of Abu Shamala and Abu Dan General Contracting Company in the Gaza Strip. The independent variable was the Blue Ocean Strategy with its four dimensions (elimination, reduction, raise, and creation), while the dependent variable was the enhancement of competitive advantage. The research addressed the extent to which the strategy contributes to strengthening the company’s competitiveness amid the challenges facing the local construction sector. The entire company staff (30 employees) participated in the study through a comprehensive survey, achieving a 100% response rate. Using a descriptive analytical approach and SPSS statistical tools—including means, standard deviations, T-test, one-way ANOVA, and multiple regression analysis—the results indicated a very high application level of the Blue Ocean Strategy (84.8%) and a similarly high level of competitive advantage (84.2%). Statistically significant relationships were found between the dimensions of elimination, raise, and creation and the competitive advantage, with the creation dimension having a direct significant effect. No significant differences appeared in respondents’ assessments of the strategy based on gender, age, qualification, or job title, while differences were significant for specialization and experience, favoring administrative and financial specializations and those with over nine years of experience. Regarding competitive advantage, no differences were observed by gender, age, or job title, but significant differences existed by educational level (favoring those with a high school education or less), specialization, and experience (favoring administrative and financial fields and those with 3–6 years or over 9 years of experience). The study recommended adopting the Blue Ocean Strategy as a permanent management approach, focusing especially on the creation dimension, and enhancing institutional innovation by empowering and training employees.

Abstract

The research aims to shed light on the concept and importance of integrated business reports, guidelines and elements of their informational content, as well as accounting disclosure in government units. The research community was represented by non-profit government units, while the research sample was chosen by the University of Baghdad as an intentional sample for the research. To achieve the goal of the research, the researchers prepared a survey form to measure the level of application of financial and non-financial indicators in the governmental unit (University of Baghdad) in the form of percentages according to the elements of the integrated report according to the (IR) version in 2021, with the use of indicators of the Global Reporting Initiative (GRI) according to its latest version In 2020 with its economic, social and environmental dimensions on the elements of the integrated report, and based on the financial and non-financial reports issued by University of Baghdad for the year 2019,The most prominent finding of the research is that the percentage level of disclosure according to the international framework for the integrated report (IR) for the governmental unit / University of Baghdad was (38%), which is a weak percentage of disclosure compared to (100%), and the researchers recommended the need for the governmental unit to adopt the International Integrated Reporting Framework ( IR ) because it provides a detailed and comprehensive presentation of all financial and non - financial information in a transparent and credible manner.

Abstract

The research aims to define the performance audit of the Reconstruction Fund for Areas Affected by War Operations, and to clarify the requirements of the INTOSAI (3000) standard for "performance audit", in line with the performance of the Reconstruction Fund, as well as to state the theoretical framework for sustainable development in terms of concept, importance, objectives, and the extent to which the objectives of the Reconstruction Fund for Areas Affected by War Operations are consistent with the Sustainable Development Goals, and to provide proposed indicators to measure the extent to which the Fund has achieved the Sustainable Development Goals and to apply a sample of the proposed indicators to verify the implementation of the Sustainable Development Goals by this Fund. The researchers relied on a set of tools that included analyzing the financial data and funding sources approved by the Fund, as well as reviewing the statistics of the projects that the Fund has worked to establish in the affected areas, in addition to the proposed indicators to verify the implementation of the Sustainable Development Goals. The research community represents the specialized development funds in Iraq, while the research sample was represented by the Reconstruction Fund for Areas Affected by War Operations to apply indicators to verify the implementation of the Sustainable Development Goals for the years 2018-2019. The research concluded that the objectives of the Reconstruction Fund for Areas Affected by War Operations are largely consistent with the development goals. Sustainable, as this fund is one of the development funds that sponsors support for the social, economic and environmental dimensions in a noticeable way.

Abstract

Given the swift digital changes occurring in the Banking industry, the purpose of this paper is to examine how well artificial intelligence systems can forecast and protect against future disasters.  By utilizing its skills in big data analytics, forecasting financial behavior, and more accurately and effectively managing risks, artificial intelligence (AI) is increasingly regarded as a crucial component in the development of banking systems and improving their operational efficiency.

 By enhancing client satisfaction, tailoring banking services to meet the demands of each individual, and cutting down on operational errors and administrative expenses, banks hope to gain a competitive edge by utilizing these technologies.  AI also helps to speed up credit decisions, make it possible to identify financial crime early, and create clever marketing plans based on forecasts of future market trends.

In order to ensure financial sustainability and achieve integration between digital transformation and the demands of banking innovation, studies show that the future of AI encompasses strategic, cultural, human, technological, and organizational dimensions in addition to technical ones.

 The paper also examined a number of anticipated long-term effects of AI applications, such as increased forecasting precision, lower operating expenses, better customer satisfaction, increased worker productivity, and assistance with investment choices.  The findings show that implementing AI applications in the banking sector is a strategic requirement to guarantee long-term growth and competitiveness in the digital era, not a technical luxury.

In order to enhance lending decisions and lower default risks, the paper also assesses how well a number of categorization algorithms work in assessing loan applicants' creditworthiness.  Using a dataset that represented the traits and financial activities of clients, seven machine learning techniques were used: Gradient Boosting, Random Forest, Extra Trees, Gaussian Naive Bayes, Logistic Regression, SVC-RBF, and KNN.

The paper used a database of 21 variables for loan applicants. Numerical variables included (age, income, credit score, debt-to-income ratio, and loan amount). Descriptive variables included (loan purpose, region, marital status, employer, educational level, and application channel). Binary variables included (whether or not the applicant had a history of default). These variables were used to predict the approval or rejection decision, with the dependent variable being represented by two values: 0 for rejection and 1 for approval.

The models were evaluated using the following six key performance indicators: Accuracy, Precision, Recall, F1 Score, Receiver Operating Characteristic Area Under the Curve (ROC AUC), and Brier Score.   The findings demonstrated that the Gradient Boosting algorithm performed best overall in both probability prediction quality and customer differentiation across different risk levels.  The Random Forest algorithm, which showed stability and balanced metrics, came next.  On the other hand, despite its moderate performance, Logistic Regression provided great interpretability, while the Gaussian Naive Bayes algorithm demonstrated high sensitivity in identifying high-risk customers.  In terms of overall accuracy and probability quality, some models—like SVC-RBF and KNN—performed worse.