«Перспективы влияния ИИ на развитие рынка «зеленого» финансирования в мировой экономике» / «Prospects for the impact of AI in the development of the green finance market in the global economy»
Аннотация
This abstract is a brief overview of the key aspects of the research conducted as part of the thesis on the impact of AI (artificial intelligence) on the green finance market in the world economy". The objective of the article is to identify the perspectives on the impact of artificial intelligence on the development of the green finance market in the global economy. The study explores the relationship between AI and green finance with a focus on ESG. The thesis consists of two main chapters that re-view the theoretical framework, analyze empirical evidence and provide recommendations on AI, green finance and sustainability in different clusters.
The topic of this thesis is extremely relevant in light of the global challenges of climate change and the need to transition to sustainable development.
First, accelerating climate change requires significant investments in green technologies and infrastructure. Green finance plays a key role in mobilizing these investments, and AI can be a powerful tool to optimize this process.
Second, traditional methods for assessing environmental risks and investment opportunities are often inefficient and time and resource intensive. AI, with its ability to process large amounts of data and identify hidden patterns, can significantly improve the efficiency and accuracy of assessing green finance risks and opportunities.
Third, the lack of transparency and accountability in financial markets creates barriers to attracting investment in green projects. AI can help improve transparency and accountability and optimize information flows in green finance.
Fourth, the uneven distribution of green finance investments, especially in developing countries, is a major barrier to achieving the Sustainable Development Goals. AI can help bridge this gap by providing access to information, resources and financial instruments that would otherwise be inaccessible to developing countries.
Fifth, integrating AI into green finance has the potential to increase the competitiveness of economies and industries that utilize green technologies and solutions. AI can help optimize production processes, minimize waste and increase resource efficiency.
Thus, the study of the prospects for the impact of AI on the development of the green finance market in the global economy is relevant and significant for the formation of a sustainable financial system to help address the global challenges of climate change and achieve sustainable development goals.
To achieve the objective, the thesis includes several main steps:
- to review the concept and the level of AI by regions;
- to consider the concept of green finance market in the global economy;
- to examine the nexus between relationship with AI adoption and green finance;
- to cluster countries based on the level of development of AI, green fi-nance market and ESG issues;
- to develop policy implications for AI and green finance implementation in various clusters and regions.
The object of this study is the countries of the world economy that use the opportunities of artificial intelligence and green finance.
The subject of the thesis is the impact of artificial intelligence and green fi-nance on the development of world economy.
The study uses a mixed-method approach, combining qualitative analysis of institutional approaches and regulations with quantitative analysis of the level of AI, a comparative analysis of tools for ESG analytics using AI, and cluster analysis. Global Green Finance Development Index, Global AI Index, and Country Sustainability Ranking (ESG) are used as indicators in the cluster analysis.
The novelty of the thesis lies in the integrated approach that combines quantitative assessment through the AI Index and qualitative data from the cluster analysis. By combining these methodologies, the study offers a distinctive approach to under-standing countries' readiness for a sustainable future with an active use of green fi-nance in an AI environment in the global economy. This study provides valuable in-sights for policy makers, businesses and stakeholders interested in utilizing green fi-nance and understanding AI and its adoption. This study provides valuable insights into the current state of the AI, green finance market in various regions. The findings contribute to the understanding of the relationship between AI, ESG and green finance. Recommendations based on the analysis can help policy makers, businesses, and stakeholders to implement effective AI adoption strategies.
The thesis consists of two main chapters, each of which includes several sub-sections dealing with specific aspects of the topic.
The research uses data from various sources, including reports and information from international organisations, including the UN, UNEP, UNDESA, OECD, Cli-mate Bonds Initiative, the World Economic Forum (WEF), stock exchanges of different countries, platforms such as INFRAGREEN, world rating agencies such as ISS ESG, various indices to assess the level of countries, companies, as well as to make a cluster analysis. The study uses both theoretical concepts and real data, which allows us to draw conclusions and recommendations that have both theoretical and practical significance.
Country-level analyses of AI, green finance and ESG indicate different levels of regional readiness. The North American region has a higher level of activity, while the average level covers Oceania, Europe, Central Asia, East Asia and the Pacific. Sub-Saharan Africa, South Asia, the Middle East, North Africa, Latin America and the Caribbean are at a lower level and require additional effort and attention to stimulate growth in these regions. The results of the study highlight the importance of targeted approaches, cooperation and knowledge sharing to accelerate development and progress in the digital world economy.
The leaders of cluster analysis are the United States and China due to the fact that these countries are the largest economies in the world. They actively invest in developments related to AI, green technologies and sustainable development. But it is important for countries to continue to develop their sustainability, which is not yet at the level of leaders. Countries need to share their valuable experience with developing and lagging countries. To show various types of support, create common plat-forms and opportunities for international cooperation.
European countries have also shown good results, they are leaders in ESG practice and must continue to innovate and cooperate in order to maintain their status at the highest level. AI and green finance are still a little more difficult for them to develop, but countries have excellent makings to start actively using them and boldly introduce new technologies.
Latin America is slowly moving to its next level of development, it already has good results in terms of green financing, not bad in ESG and still low in AI, which is what the region needs to focus on.
Oceania shows excellent results in ESG, good results in green finance, and so far, low in AI, which is what the region needs to focus on. A developed economy and a high level of income can help in this.
Sub-Saharan Africa, South Asia, Middle East and North Africa show a mixed level, but generally low in all three indicators with some average exceptions, which suggests that the regions are trying to get out of the situation they are in now. It is necessary to continue such a policy more actively, to use and ask for support and assistance from more developed regions.
Russia shows average performance in green finance and ESG, and low in AI. For development, it is necessary to strengthen the regulatory environment for "green" finance, stimulate innovation in AI, develop professional staff in the field of AI, as well as pay attention to sustainable development.
East Asia and the Pacific shows a mixed level, but at the same time, on aver-age, the region shows excellent results. Next, we need to act at the same pace, to raise low- and middle-income countries to the next level of development. It is necessary to study China's experience in the development of "green" finance and the introduction of AI, create joint projects and initiatives. Focus on the development of environmentally friendly technologies and environmental restoration projects.
International cooperation is a key success factor in the development. It is necessary to share experiences, technologies and investments. Governments must show the political will to develop these areas. It is necessary to develop sustainable development strategies, introduce regulatory mechanisms, and stimulate investment.
The topic of this thesis is extremely relevant in light of the global challenges of climate change and the need to transition to sustainable development.
First, accelerating climate change requires significant investments in green technologies and infrastructure. Green finance plays a key role in mobilizing these investments, and AI can be a powerful tool to optimize this process.
Second, traditional methods for assessing environmental risks and investment opportunities are often inefficient and time and resource intensive. AI, with its ability to process large amounts of data and identify hidden patterns, can significantly improve the efficiency and accuracy of assessing green finance risks and opportunities.
Third, the lack of transparency and accountability in financial markets creates barriers to attracting investment in green projects. AI can help improve transparency and accountability and optimize information flows in green finance.
Fourth, the uneven distribution of green finance investments, especially in developing countries, is a major barrier to achieving the Sustainable Development Goals. AI can help bridge this gap by providing access to information, resources and financial instruments that would otherwise be inaccessible to developing countries.
Fifth, integrating AI into green finance has the potential to increase the competitiveness of economies and industries that utilize green technologies and solutions. AI can help optimize production processes, minimize waste and increase resource efficiency.
Thus, the study of the prospects for the impact of AI on the development of the green finance market in the global economy is relevant and significant for the formation of a sustainable financial system to help address the global challenges of climate change and achieve sustainable development goals.
To achieve the objective, the thesis includes several main steps:
- to review the concept and the level of AI by regions;
- to consider the concept of green finance market in the global economy;
- to examine the nexus between relationship with AI adoption and green finance;
- to cluster countries based on the level of development of AI, green fi-nance market and ESG issues;
- to develop policy implications for AI and green finance implementation in various clusters and regions.
The object of this study is the countries of the world economy that use the opportunities of artificial intelligence and green finance.
The subject of the thesis is the impact of artificial intelligence and green fi-nance on the development of world economy.
The study uses a mixed-method approach, combining qualitative analysis of institutional approaches and regulations with quantitative analysis of the level of AI, a comparative analysis of tools for ESG analytics using AI, and cluster analysis. Global Green Finance Development Index, Global AI Index, and Country Sustainability Ranking (ESG) are used as indicators in the cluster analysis.
The novelty of the thesis lies in the integrated approach that combines quantitative assessment through the AI Index and qualitative data from the cluster analysis. By combining these methodologies, the study offers a distinctive approach to under-standing countries' readiness for a sustainable future with an active use of green fi-nance in an AI environment in the global economy. This study provides valuable in-sights for policy makers, businesses and stakeholders interested in utilizing green fi-nance and understanding AI and its adoption. This study provides valuable insights into the current state of the AI, green finance market in various regions. The findings contribute to the understanding of the relationship between AI, ESG and green finance. Recommendations based on the analysis can help policy makers, businesses, and stakeholders to implement effective AI adoption strategies.
The thesis consists of two main chapters, each of which includes several sub-sections dealing with specific aspects of the topic.
The research uses data from various sources, including reports and information from international organisations, including the UN, UNEP, UNDESA, OECD, Cli-mate Bonds Initiative, the World Economic Forum (WEF), stock exchanges of different countries, platforms such as INFRAGREEN, world rating agencies such as ISS ESG, various indices to assess the level of countries, companies, as well as to make a cluster analysis. The study uses both theoretical concepts and real data, which allows us to draw conclusions and recommendations that have both theoretical and practical significance.
Country-level analyses of AI, green finance and ESG indicate different levels of regional readiness. The North American region has a higher level of activity, while the average level covers Oceania, Europe, Central Asia, East Asia and the Pacific. Sub-Saharan Africa, South Asia, the Middle East, North Africa, Latin America and the Caribbean are at a lower level and require additional effort and attention to stimulate growth in these regions. The results of the study highlight the importance of targeted approaches, cooperation and knowledge sharing to accelerate development and progress in the digital world economy.
The leaders of cluster analysis are the United States and China due to the fact that these countries are the largest economies in the world. They actively invest in developments related to AI, green technologies and sustainable development. But it is important for countries to continue to develop their sustainability, which is not yet at the level of leaders. Countries need to share their valuable experience with developing and lagging countries. To show various types of support, create common plat-forms and opportunities for international cooperation.
European countries have also shown good results, they are leaders in ESG practice and must continue to innovate and cooperate in order to maintain their status at the highest level. AI and green finance are still a little more difficult for them to develop, but countries have excellent makings to start actively using them and boldly introduce new technologies.
Latin America is slowly moving to its next level of development, it already has good results in terms of green financing, not bad in ESG and still low in AI, which is what the region needs to focus on.
Oceania shows excellent results in ESG, good results in green finance, and so far, low in AI, which is what the region needs to focus on. A developed economy and a high level of income can help in this.
Sub-Saharan Africa, South Asia, Middle East and North Africa show a mixed level, but generally low in all three indicators with some average exceptions, which suggests that the regions are trying to get out of the situation they are in now. It is necessary to continue such a policy more actively, to use and ask for support and assistance from more developed regions.
Russia shows average performance in green finance and ESG, and low in AI. For development, it is necessary to strengthen the regulatory environment for "green" finance, stimulate innovation in AI, develop professional staff in the field of AI, as well as pay attention to sustainable development.
East Asia and the Pacific shows a mixed level, but at the same time, on aver-age, the region shows excellent results. Next, we need to act at the same pace, to raise low- and middle-income countries to the next level of development. It is necessary to study China's experience in the development of "green" finance and the introduction of AI, create joint projects and initiatives. Focus on the development of environmentally friendly technologies and environmental restoration projects.
International cooperation is a key success factor in the development. It is necessary to share experiences, technologies and investments. Governments must show the political will to develop these areas. It is necessary to develop sustainable development strategies, introduce regulatory mechanisms, and stimulate investment.