The paper explores the impact of digital payment systems, blockchain technology, and AI/machine learning on innovation and sustainability in financial organizations. As part of the analysis, the study has adopted an explanatory research design and has used SmartPLS in order to analyze the data collected from 230 professionals of different fields through a structured questionnaire. The results show positive effects of digital payment systems and blockchain technology on organizations’ innovations with the impact of digital payments being the most pronounced. Empirical results suggest that these technologies are important to improve sustainability performance, depending on measures of internal consistency and discriminant validity among the proposed constructs. Al, also machine learning, has the highest relevance with environmental sustainability, thereby underlining the importance and work of such measures. Based on the Resource-Based View (RBV) theory, the study also explains the need for the organization to assimilate these innovations to enhance the organizational operations, customer satisfaction, and compliance with the laws. The study highlights fintech’s potential to address environmental issues and enhance societal goals, but geographical limitations may obstruct its transportability.

Artificial intelligence (AI) is increasingly utilized in different industries, particularly financial services, where it handles functions traditionally performed by humans, yet a significant gap exists in understanding its real-world applications in corporate reporting. This research purposes to contribute to the financial process and finance literature by reviewing comprehensively how previous literature have addressed the topic of Artificial Intelligence and its Applications in financial process and Finance. This study aims to address these gaps through conducting a bibliometric analysis, focusing on peer-reviewed articles from 2010 to 2024. The study's findings highlighted a marked increase in research output, particularly during the COVID-19 pandemic, highlighting the integration of AI in financial and financial process research by enhancing accuracy and reducing errors in financial reporting. The analysis highlighted a collaborative effort among researchers, primarily from China and the United States, for the advancements in this field. AI dominates financial process and finance research, with key terms like machine learning, blockchain, big data, and deep learning highlighting a multidisciplinary approach to enhance efficiency and decision-making. However, challenges such as data protection and ethical considerations remain prevalent. The findings and discussions emphasized the need for new regulatory frameworks and skill development for professionals to adapt to these technological changes. Future research should explore the implications of AI on corporate governance and accountability, providing a way for innovative practices in the industry. This study contributed valuable insights into AI's transformative potential, providing practitioners and policymakers with knowledge to navigate the evolving landscape of finance and Financial Process.

This paper investigates the relationship between green finance, foreign direct investment (FDI), and renewable energy consumption (REC) on economic growth in the Middle East, a region that is historically reliant on fossil fuels. This study aims to assess how these factors contribute to sustainable development amid growing global interest in energy efficiency and climate change mitigation. Using panel data analysis from 2000 to 2023, the study integrates the endogenous growth theory and the environmental Kuznets curve to evaluate the short- and long-term effects of green initiatives on economic performance. The findings reveal that renewable energy and green finance drive economic growth significantly, while FDI plays a pivotal role in facilitating technological advancements and boosting productivity. This study highlights the potential for a sustainable economic model in the Middle East, offering valuable insights for policymakers focusing on transitioning toward FDIs, renewable energy, and green finance to achieve long-term environmental and economic goals.

This study aimed to identify the effect of applying internal control elements in accordance with International Auditing Standard No. 315 and the COSO framework (control environment, risk assessment, control activities, information, communication, and control) on reducing tax evasion activities. The study population consisted of Jordanian telecommunications companies; the sample of the study included financial managers, accountants, and internal auditors working in Jordanian telecommunications companies, where a dedicated questionnaire was developed for this purpose and distributed to them. The questionnaire was administered using the comprehensive survey technique by distributing 46 copies of the questionnaire to the study participants. The findings were analyzed using descriptive and inferential statistical methods, utilizing Statistical Package for Social Sciences. Through a field study involving various telecommunication operators in Jordan, this research aims to examine the practical implementation of IAS 315 and its implications for fostering a transparent and compliant tax reporting environment. The findings strongly support this investigation, as evidenced by a high correlation coefficient of 0.886 and an R² value of 0.785, indicating that the internal control elements account for 78.5% of the variance in reducing tax evasion. Significant individual predictors positively impact reducing tax evasion. The outcome of this study is expected to contribute to the broader discourse on financial ethics and governance, particularly in emerging markets where regulatory compliance is crucial for economic stability and growth.

Integrated reporting (IR) has become a groundbreaking model that connects both financial and non-financial reporting in order to promote corporate transparency and value generation. Nonetheless, variations in implementation, governance frameworks, and digital integration constrain its effectiveness. This paper seeks to review the current trends in IR in the framework of the convergence of environmental, social, and governance (ESG), digital transformation, and Industry 5.0. Major academic databases were used to analyse 48 studies on the PRISMA method that were published between 2024 and 2025. It is found that technologies like artificial intelligence (AI), natural language processing (NLP), and blockchain can considerably enhance reporting accuracy and timeliness, but add ethical, regulatory, and standardisation issues. Quality of governance, diversity of boards, and ethical responsibility turn out to be key forces behind IR credibility. The paper concludes that IR is shifting from a symbolic tool of compliance to a strategic governance tool that is in line with stakeholder-centric and sustainability-oriented models. The study is an addition in that it incorporates digital ethics and governance innovation into the IR debate and provides policy-makers and organisations with harmonized and transparent reporting systems.