This book shows latest research on artificial intelligence for sustainable technology. ICGER 2021 was organized by the Accounting, Finance and Banking Department at Ahlia University, Bahrain, and was conducted on the 15th and 16th of September. The strategic partners included the University of Jordan, the Bahrain Economists Society, the Association of Chartered Certified Accountants: ACCA, Al-Barka Banking Group and the International Computer Auditing Education Association: ICAEA . The theme of the ICGER 2021 centered around artificial intelligence for sustainable finance and sustainable technology. Accordingly, the papers presented at the conference provided a holistic view of sustainable finance, sustainability, AI, financial technology, cybersecurity, blockchain, CSR, and governance. This book, unlike ever before, brings together intelligence applications of new technologies and the sustainability requirements in the era of the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI applications and financial technologies to develop future strategies and to achieve sustainable development goals.

Artificial Intelligence for Sustainable Value Creation provides a detailed and insightful exploration of both the possibilities and the challenges that accompany widespread Artificial Intelligence

This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

This edition of the OECD Sovereign Borrowing Outlook reviews developments in response to the COVID-19 pandemic for government borrowing needs, funding conditions and funding strategies in the OECD area.

The crucial challenge of integrating sustainability into business and investment decisions is compounded by the complexity of analyzing vast and intricate datasets to make informed choices. Traditional approaches often fail to provide timely and accurate insights into environmental, social, and governance (ESG) factors, hindering progress toward a greener future. Additionally, the rapid evolution of AI and machine learning in finance has left many professionals needing help to grasp their full potential in advancing sustainability goals. With a comprehensive understanding and practical guidance, organizations can stay caught up in adopting sustainable practices and leveraging AI for financial and environmental benefits. Social and Ethical Implications of AI in Finance for Sustainability offers a timely and comprehensive solution to these challenges by thoroughly examining how AI can safely enhance sustainability in finance. The book bridges the gap between theory and practice, offering practical insights and real-world applications to empower academics, practitioners, policymakers, and students. Through a series of expertly curated chapters, readers will gain a deep understanding of the role AI plays in reshaping finance for a sustainable future. The book's instructional elements, including case studies and expert analysis, provide a roadmap for incorporating AI into sustainability strategies, enabling organizations to make informed decisions and drive positive change.

This new book provides a valuable overview of how artificial intelligence (AI) applications are transforming global businesses and financial organizations, looking at the newest artificial intelligence-based solutions for e-commerce, corporate management, finance, banking and trading, and more. Chapters look at using AI and machine learning techniques to forecast and assess financial risks such as liquidity risk, volatility risk, and credit risk. The book also describes the use of natural language processing and text mining paired with machine learning models to assist in guiding sophisticated investors and corporate managers in financial decision making. Other topics include cryptocurrency in emerging markets; the role of artificial intelligence in making a positive impact on sustainable development; the use of fintech for micro, small and medium enterprises; the role of AI i financial education; the application of artificial intelligence in cyber security; and more.

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation. - Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment - Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum - Addresses the advanced field of renewable generation, from research, impact and idea development of new applications

This book tells the story of how the convergence between corporate sustainability and sustainable investing is now becoming a major force driving systemic market changes. The idea and practice of corporate sustainability is no longer a niche movement. Investors are increasingly paying attention to sustainability factors in their analysis and decision-making, thus reinforcing market transformation. In this book, high-level practitioners and academic thought leaders, including contributions from John Ruggie, Fiona Reynolds, Johan Rockström, and Paul Polman, explain the forces behind these developments. The contributors highlight (a) that systemic market change is influenced by various contextual factors that impact how sustainable investing is perceived and practiced; (b) that the integration of ESG factors in investment decisions is impacting markets on a large scale and hence changes practices of major market players (e.g. pension funds); and (c) that technology and the increasing datafication of sustainability act as further accelerators of such change. The book goes beyond standard economic theory approaches to sustainable investing and emphasizes that capitalism founded on more real-world (complex) economics and cooperation can strengthen ESG integration. Aimed at both investment professionals and academics, this book gives the reader access to more practitioner-relevant information and it also discusses implementation issues. The reader will gain insights into how "mainstream" financial actors relate to sustainable investing.

As the world increasingly recognizes the importance of sustainability, businesses and investors are looking for ways to integrate sustainable practices into their operations and investment decisions. At the same time, advancements in artificial intelligence (AI) and technology are transforming the finance industry and are enabling more data-driven decision-making. The intersection of these fields presents a significant opportunity to accelerate progress towards a more sustainable future, while also improving financial performance. This book explores the crucial role of AI in sustainability and finance, examining how financial technologies and machine learning are shaping the approach of finance professionals towards environmental, social, and governance (ESG) issues. It provides a comprehensive and integrated perspective on how these areas are becoming increasingly intertwined and examines the ethical and social implications of AI in finance and its potential to unlock new opportunities for sustainability. By focusing on the practical implications of these intersections and including both case studies and expert analysis, the book provides valuable insights for practitioners, policymakers, academics, and students alike.