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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
This book showcases research, theoretical, and validated work associated with digital finance to enhance the quality of a more sustainable environment.
The primary objective of Fintech for ESG and the Circular Economy is to evaluate how fintech advancements and sustainable practices effectively drive transformative and sustainable change. It aims to motivate individuals with ideas and discussions to promote financial technology and foster creativity for a more sustainable and equitable future.
The book delves into the intersection of technology and sustainability, offering insights into how big data, machine learning, and blockchain technology are transforming ESG practices and the circular economy. It highlights the potential of FinTech to drive sustainable finance, explores the current role of cyber ecosystems and digital currencies in sustainable finance, and examines the intricate legal landscape surrounding green finance in India. The book also discusses the influence of ESG factors on financial decision-making and the integration of sustainability metrics into financial analysis, supported by examples of how companies and investors are adopting these practices.
Additionally, the book explores the role of financial institutions in enabling crowdfunding platforms, particularly in African markets, and provides case studies that demonstrate their impact on financial inclusion and entrepreneurship. It also analyzes the legal implications of blockchain and smart contracts within FinTech, the convergence of digital business models with ESG principles, and the role of digital currencies in promoting financial inclusion and sustainable economic growth, particularly in India. The book concludes with an exploration of tokenomics and its potential to incentivize sustainable behaviors, and examines how digital finance innovations in Tanzania are improving financial inclusion by overcoming barriers to financial services for the unbanked population.
Audience
This book will be of interest to scholars, researchers, academicians, and students of commerce, banking, finance, sustainability, and financial technology. This book is helpful for business professionals, researchers, and technical industry workers in finance and artificial intelligence.
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Seitenzahl: 477
Veröffentlichungsjahr: 2024
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Table of Contents
Cover
Table of Contents
Series Page
Title Page
Copyright Page
Dedication Page
Preface
Acknowledgments
1 Data-Driven Sustainability: Unlocking the Potential of Machine Learning and Big Data for ESG Integration & the Circular Economy
1.1 Introduction to Big Data and Machine Learning
1.2 Environmental, Social, and Governance (ESG)
1.3 Circular Economy
1.4 ESG and Circular Economy Integration
1.5 Future Trends and Challenges in ESG and Circular Economy
References
2 Blockchain Technology and Its Potential in Sustainable Finance and Investment
2.1 Introduction
2.2 Literature Review
2.3 Role of Blockchain Technology in Sustainable Finance and Investment
2.4 Challenges of Blockchain Technology
2.5 Conclusion
2.6 Implications
2.7 Suggestion and Recommendations
References
3 The Relationship Between FinTech and Financial Sustainability: Turkey Case
3.1 Introduction
3.2 The Framework for FinTech and Financial Sustainability
3.3 The Profile of FinTech in Turkey
3.4 Conclusion
References
Websites
4 Leveraging FinTech for the Advancement of Circular Economy
4.1 Introduction
4.2 The Circular Economy - FinTech Linkage
4.3 FinTech-Driven Triumphs of Circular Economy
4.4 FinTech-Related Challenges that Hinder Circular Economy
4.5 Conclusion
References
5 Cyber Ecosystem and Digital Currency: Review and Current Status
5.0 Introduction
5.1 Digital Currency in Other Countries
5.2 Types of Digital Currency
5.3 Arguments in Favor of Digital Currency
5.4 Arguments - Why Digital Currency Must be Discouraged
5.5 Attack on the Banking System
5.6 What are the Biggest Threats to Digital Currency?
5.7 Why are Indian Banking Organizations Targeted?
5.8 How to Reduce the “Security Threats” in the Banking Sector?
5.9 Conclusion
References
6 Navigating the Legal Landscape of Green Finance and Responsible Investment in India: A Critical Analysis
6.1 Introduction
6.2 Legal Framework Governing Green Finance and Investment in India
6.3 Certain Indian Companies Engaged in Green Financing and Responsible Investment
6.4 Interface of Sustainable Development Goals and Green Finance
6.5 CSR Rules and Companies Act, 2013, and Environmental Justice
6.6 Greenwashing: A Challenge to Honest Implementation of Green Bond
6.7 Implications of Regulating Sources of Green Financing on Policymakers, Business Houses, and Society
6.8 Conclusion and Recommendations
References
7 Impact of Environmental, Social, and Governance (ESG) and the Circular Economy (CE) on Financial Decision-Making
7.1 Introduction
7.2 The Mandate for ESG and Circular Economy Global Goals
7.3 Organizations Impacting Sustainability Reporting and Financial Governance
7.4 Financial Policies and Strategies of Asset Owners, Banks, and Other Financial Firms
7.5 Impact of ESG and Circular Economy on Financial Decisions of Banks and Financial Intermediaries
7.6 Impact of ESG and Circular Economy on Financial Decisions of Firms
7.7 Impact of ESG and Circular Economy on Decisions to Use Financial Technology (FinTech)
7.8 Concluding Remarks
References
8 Institutions and Crowdfunding Success in Africa
8.1 Introduction
8.2 Literature Review and Hypothesis Development
8.3 Methodology and Data
8.4 Results and Discussion
8.5 Conclusion and Policy Implications
References
9 Legal Aspects of Smart Contracts and Application of Blockchain Technology in FinTech
9.1 Introduction
9.2 Discussion and Conclusion
References
10 ESG Excellence in the Digital World: Circular Economy E-Business Solutions
10.1 Introduction
10.2 Literature and Theoretical Background
10.3 Research Methodology
10.4 Discussion and Recommendations
10.5 Conclusion
References
11 Role of FinTech in Fueling Social Change: A Field Study
11.1 Introduction
11.2 Factors Behind the FinTech Usage in Taksal and Pabri
11.3 Impact of FinTech on the Lives of Respondents of Taksal and Pabri
11.4 Conclusion
References
12 Significance of Digital Currencies in Sustainable Finance and Investment—An Indian Perspective
12.1 Digital Money
12.2 Role of The Reserve Bank of India in Fostering Financial Inclusion through Digital Transformation of Financial Services
12.3 Role of CBDCs in Digital Financial Transformation
12.4 Digital Rupee e₹ Story of India
12.5 Significant Role Played by Digital Currencies in Supporting Green and Sustainable Finance
12.6 Potential Risk Involved in Digital Currencies
References
13 A Leap Towards Tokenomics: The Future of Sustainability
13.1 A Few Words on Tokenomics
13.2 Opportunities Presented by Tokenomics
13.3 The “Economics” in Tokenomics
13.4 Challenges with Tokenomics
13.4 Tokenomics in the Indian Context
13.6 Conclusion
References
14 Advancing Financial Inclusion through Digital Finance Innovations in Tanzania
14.1 Introduction
14.2 Literature Review
14.3 Research Methods
14.4 Results and Discussions
14.5 Conclusion
References
Index
End User License Agreement
List of Tables
Chapter 3
Table 3.1 Some important FinTech companies in Turkey.
Chapter 5
Table 5.1 Empathy chart to describe the quality of service in banks [21].
Chapter 6
Table 6.1 Certain companies issuing green bonds in India till 2020 (Bagaria, 2...
Chapter 7
Table 7.1 Summary of organizations leading the ESG and circularity agenda.
Table 7.2 Examples of ESG and circular economy projects.
Chapter 8
Table 8.1 Variable definition.
Table 8.2 Descriptive statistics.
Table 8.3 Matrix of correlations and VIF
5
.
Table 8.4 Crowdfunding and institutions.
Table 8.5 Crowdfunding and institutions: Economic growth channel.
Table 8.6 Marginal effect.
Chapter 14
Table 14.1 The findings of some previous studies.
List of Illustrations
Chapter 1
Figure 1.1 The role of big data and machine learning in sustainability.
Figure 1.2 ESG reporting frameworks.
Chapter 3
Figure 3.1 Important terms in FinTech.
Figure 3.2 The FinTech ecosystem in Turkey.
Chapter 5
Figure 5.1 Pictorial representation of cryptocurrency [14].
Figure 5.2 Samples of a digital currency issued by the government of India [...
Figure 5.3 Distribution of banking players in Indian systems [25].
Figure 5.4 Graph depicting the status of online banking vs physical banking ...
Figure 5.5 Cybersecurity Niti Ayog report [31].
Figure 5.6 Number of fraud cases vs amount involved as per RBI report [32]....
Figure 5.7 Graph showing fraud committed in leading banks in India [34].
Figure 5.8 Status of different bank frauds in India [39].
Figure 5.9 Ratio depiction of different security attacks in financial organi...
Figure 5.10 Graph showing a global number of people who lost money in bank-r...
Figure 5.11 Graph showing the monetary loss in financial transactions [45]....
Figure 5.12 Awareness of NIST framework [48].
Figure 5.13 Canara bank e-payment page hacked and claimed by a Pakistani gro...
Figure 5.14 Different actions asked by scamsters to do for stealing sensitiv...
Chapter 6
Figure 6.1 SDGs focused on climate mitigation.
Chapter 7
Figure 7.1 Relationships driving ESG and circular economy in financial decis...
Figure 7.2 Breakdown of the DuPont model.
Figure 7.3 Financial ratios impacted by ESG and circular economy projects.
Figure 7.4 Impact of ESG and circular economy on a firm’s investments.
Chapter 8
Figure 8.1 Control of corruption.
Figure 8.2 Government effectiveness.
Figure 8.3 Political stability.
Figure 8.4 Regulation quality.
Figure 8.5 Rule of law.
Figure 8.6 Voice and accountability.
Chapter 12
Figure 12.1 Preferred mode of transaction and preferred mode of small value ...
Figure 12.2 Future consideration for CBDC in India.
Figure 12.3 Potential future use cases for CBDC in India.
Chapter 13
Figure 13.1 Identification of payment token vis-à-vis utility token.
Chapter 14
Figure 14.1 Promoting financial inclusion through Digital Financial Services...
Figure 14.2 A research framework highlighting the study’s systematic method...
Guide
Cover Page
Table of Contents
Series Page
Title Page
Copyright Page
Dedication Page
Preface
Acknowledgments
Begin Reading
Index
WILEY END USER LICENSE AGREEMENT
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Scrivener Publishing100 Cummings Center, Suite 541JBeverly, MA 01915-6106
Fintech in a Sustainable Digital Society
Series Editors: Ernesto DR Santibanez Gonzalez and Prasenjit Chatterjee
New and disruptive financial strategies and practices based on technology are key to reduce carbon emissions and save the planet. By establishing new sustainable cross-industry ecosystems and business models, the series “Fintech in a Sustainable Digital Society” aims to get a deeper understanding of fintech, insurtech, and blockchain at the intersection of sustainability. It also covers application-focused research in fintech perspectives on AI, cloud computing, machine learning, optimization, and scientific computing. The series disseminates monographs and edited volumes concentrating on all new fintech fields.
Publishers at ScrivenerMartin Scrivener ([email protected]) Phillip Carmical ([email protected])
Fintech for ESG and the Circular Economy
Edited by
Ernesto D.R. Santibanez Gonzalez
University of Talca, Chile
Vinay Kandpal
Dept. of Management Studies, Graphic Era University, Dehradun, India
Peterson K. Ozili
Central Bank of Nigeria
and
Prasenjit Chatterjee
Dept. of Mechanical Engineering, MCKV Institute of Engineering, West Bengal, India
This edition first published 2024 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA© 2024 Scrivener Publishing LLCFor more information about Scrivener publications please visit www.scrivenerpublishing.com.
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Library of Congress Cataloging-in-Publication Data
ISBN 978-1-394-23396-0
Cover image: Pixabay.ComCover design by Russell Richardson
The editors would like to dedicate this book to their parents, life partners, children, students, scholars, friends, and colleagues.
Preface
In an era where technological advancement and sustainability form the twin pillars supporting the future of finance, this volume presents a timely exploration of the intersection between financial technology (FinTech), Environmental, Social, and Governance (ESG) criteria, and the circular economy. This book originated from a shared recognition of the pressing need for inventive remedies in response to worldwide environmental and societal difficulties. This manuscript represents a compilation of ideas, research, and practical knowledge contributed by a diverse group of experts who share a common goal: to utilize FinTech in the promotion of ESG objectives and to support the principles of the circular economy.
Each chapter delves into the complexities and nuances of its topic, from the granular details of machine learning algorithms in ESG analytics to the broader impacts of blockchain on sustainable finance. Chapter 1 sets the foundation, exploring the role of big data and machine learning in enhancing ESG practices within the framework of a circular economy. This leads to a detailed analysis in Chapter 2 of how blockchain technology is not just a tool but a potential game-changer in fostering sustainable finance and investment strategies. The focus then shifts from the global to the particular, with Chapter 3 examining the specific dynamics within Turkey’s financial ecosystem, before scaling back to a broader view in Chapter 4, which explains how to leverage FinTech to advance the circular economy.
The scope of Chapter 5 is on how cyber ecosystems and digital currencies capture the current state of play in sustainable finance, while Chapter 6 navigates the intricate legal landscape of green finance in India, providing a critical analysis of the challenges and opportunities that lie ahead. The seventh chapter discusses how ESG factors and the principles of the Circular economy influence the financial decision-making process. It covers how companies and investors integrate sustainability metrics into their analyses and the financial instruments that support these considerations. In Chapter 8, we explore the role of financial institutions in enabling crowd-funding platforms and their success in African markets, with examples of regulatory environments, technological infrastructure, and case studies that demonstrate the impact of crowdfunding on financial inclusion and entrepreneurship.
Chapter 9 delves into the legal implications of using blockchain and smart contracts within the FinTech sector. It examines the challenges and opportunities of smart contracts in financial services, including compliance, enforcement, and the evolving legal landscape. In Chapter 10, the convergence of digital business models with ESG excellence is highlighted, with an overview of how e-businesses can adopt circular economy principles to enhance sustainability, reduce waste, and create value in the digital age. Chapter 11 presents case studies on how FinTech initiatives have driven social change, with examples of financial products and services that have had a social impact, discussing both successes and lessons learned.
Focusing on India, Chapter 12 analyzes the role of digital currencies in sustainable finance and investment within the country. It discusses the potential of cryptocurrencies and central bank digital currencies (CBDCs) in promoting financial inclusion and supporting sustainable economic growth. Chapter 13 explores tokenomics, which involves studying the economic principles governing cryptocurrency tokens, and analyzes its implications for sustainability. This chapter investigates how token-based systems incentivize sustainable behaviors and contribute to the development of green economies. Finally, Chapter 14 examines the specific case of Tanzania and how digital finance innovations are leveraged to improve financial inclusion. It covers mobile money platforms and digital banking and how these technologies overcome barriers to financial services for the unbanked population.
The EditorsJune 2024
Acknowledgments
The editors wish to express their warm thanks and deep appreciation to those who provided valuable input, support, constructive suggestions, and assistance in editing and proofreading of this book.
The editors would like to thank all the authors for their valuable contributions in enriching the scholarly content of the book.
Mere words cannot express the editors’ deep gratitude to the entire editorial and production teams of Scrivener Publishing, particularly Martin Scrivener for his great support, encouragement, and guidance all through the publication process. This book would not have been possible without his significant contributions.
The editors would like to sincerely thank the reviewers who kindly volunteered their time and expertise to shape such a high-quality book on a very timely topic.
The editors wish to acknowledge the love, understanding, and support of their family members during the book’s preparation.
Finally, the editors use this opportunity to thank all the readers and expect that this book will continue to inspire and guide them in their future endeavors.
The Editors
1Data-Driven Sustainability: Unlocking the Potential of Machine Learning and Big Data for ESG Integration & the Circular Economy
Priya Soni
School of Business & Commerce, Department of Business Administration, Manipal University, Dehmi Kalan, Off Jaipur-Ajmer Expressway, Jaipur, Rajasthan, India
Abstract
The paradigm of sustainable development has assumed a central position in international agendas as the globe faces rising difficulties brought on by climate change, resource depletion, and environmental degradation. Environmental, social, and governance (ESG) principles have become crucial indicators in this environment for evaluating the sustainability and moral implications of corporate practices. Achieving long-term ecological balance also requires the adoption of circular economy techniques, which put a premium on reducing waste and improving resource efficiency.
The revolutionary potential of big data and machine learning (ML) technologies is thoroughly explored in this chapter with a view to promoting ESG objectives and accelerating the shift to a circular economy. These innovative technologies’ confluence presents unheard-of prospects for the analysis of huge, complicated information, the extraction of insightful conclusions, and the facilitation of datadriven decision-making for sustainable practices.
Organizations may acquire a thorough insight into their sustainability performance by using extensive data sources that include environmental impacts, social responsibility indexes, and corporate governance frameworks. By recognizing patterns, forecasting future trends, and evaluating risk factors, ML algorithms further improve predictive skills, enabling stakeholders to execute proactive sustainability policies.
Circular economy activities may be optimized to reduce waste creation, enhance recycling procedures, and support circular product design through the intelligent processing of various datasets linked to material lifecycles, supply chain management, and product consumption patterns. ML models allow for dynamic demand forecasting, adaptive resource allocation, and the development of closed-loop systems that promote resource conservation and sustainable growth.
In summary, the application of big data and ML to the circular economy and ESG provides a paradigm-shifting step toward a sustainable future. Businesses, decision-makers, and stakeholders may make wise choices, track development, and collaborate to meet global sustainability targets by leveraging the power of data-driven insights. To guarantee that these breakthroughs function as agents of change in the effort to create a regenerative and socially responsible society, it is necessary to strike a careful balance between technical developments and ethical considerations.
Keywords: Big data, machine learning, ESG (environmental, social, and governance), circular economy, sustainability, ethical business practices
1.1 Introduction to Big Data and Machine Learning
The amount of data produced from many sources has increased tremen-dously in today’s linked society. Big data, a massive collection of data, offers enormous potential for businesses to learn important lessons and make wise decisions. However, the complexity and size of big data cannot be handled by the conventional methods of data analysis and processing. Herein lies the application of machine learning (ML), a branch of artificial intelligence.
The phrase “Big data” refers to extremely large and intricate data sets that are too complex for standard data processing software to handle, store, and analyze efficiently. These datasets are defined by the three Vs: variety (both organized and unstructured), velocity (fast data creation), and volume (huge amounts of data). Big data is information gathered from a wide range of sources, such as sensors, social media, transactional records, and more (Wang, 2020) [1].
Contrarily, the artificial intelligence discipline of ML enables computer systems to learn from data without explicit programming. ML algorithms employ patterns in the data to enhance their performance over time rather than depending on predetermined rules. These algorithms can find hidden patterns, anticipate the future, and change their behavior on the fly in response to input [2].
Numerous industries, including banking, healthcare, marketing, and transportation, have undergone radical change because of the union of big data and ML. Their combined strength enables organizations to analyze enormous volumes of data, resulting quickly and effectively in more accurate decision-making, improved customer experiences, and the identification of profitable possibilities.
As companies and organizations try to strike a balance between economic development, environmental preservation, and social responsibility, sustainability has become a crucial worldwide concern. Big data and ML are crucial to the advancement of sustainability initiatives because they offer strong tools for gathering, analyzing, and drawing conclusions from vast volumes of data (Wang, 2020) [3]. The following are some significant ways that these technologies promote sustainability:
Data-Driven Decision Making: Big data enables businesses to collect and analyze significant amounts of data from a variety of sources, including supply chain records, social media, satellite imaging, and environmental sensors. These data may be processed by ML algorithms, which can then spot trends and produce insightful findings. These revelations make it possible to make decisions based on facts in fields like resource management, energy efficiency, waste minimization, and sustainable product design (Mishra, 2019) [4].
Environmental Monitoring and Management: Real-time monitoring of environmental factors including air quality, water quality, and biodiversity is made possible by big data and IoT (Internet of Things) devices. These data may be processed by ML algorithms to find abnormalities, forecast environmental changes, and maximize resource use. This aids in effective pollution management, early warning systems for natural catastrophes, and ecosystem preservation (Mishra, 2019) [5].
Supply Chain Transparency: Big data may provide businesses with complete insight into their supply chains, allowing them to follow the flow of products and raw materials from their point of origin to their destination. This data may be analyzed by ML to detect possible dangers, evaluate the social and environmental effects of supply chain operations, and assist sustainable sourcing techniques.
Energy efficiency and smart grid management are made possible by big data analytics and ML, which may be used to optimize energy usage patterns, forecast demand changes, and operate smart grids. As a result, there is less energy wasted, more dependence on renewable energy sources, and an energy infrastructure that is more durable (Grattieri, 2020) [6].
Integration of the Circular Economy: Figure 1.1 provides evidence of the integration of techniques such as big data, deep learning, and machine learning, which can help facilitate the shift to a model based on product lifecycles, consumer behavior, and waste streams. These technologies can spot chances for material recovery, recycling, and remanufacturing, reducing waste and fostering environmentally friendly manufacturing methods.
Figure 1.1 The role of big data and machine learning in sustainability.
Big data and ML are useful tools for measuring the social effect of corporate operations and activities. Organizations may better understand the mood and perception of their stakeholders and use these insights in their social responsibility practices by analyzing data from social media, consumer reviews, and staff surveys.
Predictive Analytics for Climate Change: The phenomena of climate change are dynamic and complicated. Big data and ML algorithms may examine past weather patterns, climate data, and other pertinent information to anticipate potential future climate scenarios. The creation of adaptable solutions and laws to lessen the effects of climate change benefits greatly from these ideas.
Environmental, Social, and Governance (ESG) and Circular Economy: Circular economy and environmental, social, and governance (ESG) are two interrelated frameworks that direct companies and organizations toward ethical behavior. These frameworks have become increasingly important in recent years as businesses have realized how important it is to take into account not just their financial success but also their effects on society, the environment, and corporate governance.
1.2 Environmental, Social, and Governance (ESG)
Environmental: The “E” in ESG stands for environmental impact and management of a company’s interaction with the environment. This includes initiatives to control waste and pollution, lower carbon emissions, conserve resources, encourage the use of renewable energy sources, and more. Companies are rated according to how committed they are to sustainability and how eco-friendly they are.
Social: The “S” in ESG stands for a company’s social effect and its interactions with different stakeholders, such as its workers, clients, suppliers, and neighbors. Fair labor practices, employee well-being, diversity and inclusion, community involvement, and contributions to society’s welfare are all examples of social elements.
Corporate governance and the framework that monitors a company’s activities are the “G” and “G” in ESG. This covers things like board impartiality, openness, accountability, executive pay, anti-corruption safeguards, and adherence to moral standards.
Strong ESG performers seek to maximize long-term value while minimizing harm to society and the environment. Investors and stakeholders are increasingly using ESG criteria to evaluate the sustainability and ethical standards of the firms they invest in or work with.
1.3 Circular Economy
An economic strategy known as the “circular economy” aims to separate economic expansion from the depletion of limited resources. Through recycling, reusing, and remanufacturing, it seeks to eliminate waste and prolong the useful life of goods, materials, and resources. The notion of imitating natural systems, where waste from one process becomes a resource for another, is what gave rise to the concept (Ma and Dai, 2020) [7].
The following are important circular economy tenets:
Creating things with extended life and repairability
Encouraging goods rental and sharing above ownership
Facilitating material recovery and recycling
Promoting the use of sustainable resources
Reducing waste production over the whole value chain
The circular economy stimulates innovation, generates new business possibilities, and boosts economic resilience in addition to reducing the environmental effect of production and consumption.
1.4 ESG and Circular Economy Integration
ESG and circular economy are intertwined in sustainability initiatives. As it encourages resource efficiency, waste reduction, and sustainable product design, adopting circular economy concepts can have a beneficial influence on a company’s environmental performance (E). Since circular economy practices can strengthen social fairness and working conditions, they also have an impact on social aspects (S). By making thoughtful decisions and planning, governance (G) is strengthened in accordance with ethical and sustainable governance principles.
1.4.1 Machine Learning Applications for Sustainable Practices
Applications of ML may significantly advance and promote sustainable practices in a variety of industries. Here are some ways that ML might support sustainability:
Energy Optimization: ML algorithms can analyze data from sensors and devices to reduce the amount of energy used in manufacturing processes, transportation networks, and buildings. ML can recommend energy-effi t practices and lower carbon footprints by spotting patterns and trends.
Predictive Maintenance: ML can be used in industries to forecast equipment breakdowns and maintenance requirements. This proactive strategy minimizes resource waste, downtime, and unexpected malfunctions.
Management of Smart Grids: By anticipating energy demands and balancing renewable and conventional energy sources, ML may assist manage power distribution in smart grids. This optimization promotes energy efficiency and lessens reliance on non-renewable resources.
Climate Prediction and Adaption: ML models can analyze climate data, forecast extreme weather, assist adaption plans, and provide early warning systems.
Precision Agriculture: agricultural practices may be improved by analyzing data from sensors, satellites, and weather stations. Insights regarding crop trends, water use, and soil health are provided by ML, which aids in boosting agricultural output while consuming fewer resources.
Trash Management: ML may be used to streamline the procedures for sorting and recycling trash. Recycling materials may be recognized using image recognition algorithms, improving trash sorting and resource recovery.
Sustainable Supply Chains: To develop SSC, ML may evaluate the environmental and social practices of suppliers. Businesses may choose suppliers more wisely by researching supplier performance and compliance data (Borade, 2020) [8].
Environmental Monitoring: To monitor and evaluate the state of the environment, ML models may analyze data from sensors, drones, and satellites. Among other things, this information may be used to manage air quality, monitor deforestation, and save animals. Green Building Design: ML can help with green building design by simulating energy performance, optimizing layouts, and suggesting eco-friendly materials.
Circular Economy: By examining customer behavior and supply chain data to promote recycling, product refurbishing, and reuse, ML can aid in the transition to a circular economy.
Businesses, governments, and organizations may use the power of ML to make data-driven choices that support sustainable practices, lessen environmental consequences, and contribute to a future that is more sustainable. To get the best outcomes in sustainability applications, it is vital to make sure that the data used to train ML models is accurate, representative, and devoid of bias.
1.4.2 Circular Economy Implementation with Big Data and Machine Learning
Big data and ML use in a circular economy may greatly improve the efficacy and efficiency of circular practices. These are a few applications for these technologies like managing waste and recycling in which big data may be used to monitor and analyze the rates of garbage creation, collection, and recycling across various geographic areas. To cut down on transportation emissions, ML systems can anticipate garbage amounts, use image recognition to find recyclable products in the waste stream, and optimize waste collection routes. In addition, big data may be used to collect information on a product’s complete lifespan, including its raw ingredients, manufacturing processes, usage trends, and end-of-life care. ML may examine this data to find areas where product design might be enhanced, durability could be increased, and recycling could be made easier.
Moreover, reverse logistics and remanufacturing facilitate the effective return, refurbishing, and remanufacturing of goods and components, big data and ML may help manage reverse logistics (Durand, 2019) [9]. ML algorithms can streamline the process of choosing whether to recycle, remanufacture, or fix a piece of equipment. In terms of predictive maintenance, ML algorithms can analyze data from embedded sensors and linked devices in things like equipment and appliances. Businesses may increase product lifespans by anticipating maintenance requirements, lowering the need for premature replacements, and preserving resources.
Big data and ML may be used to analyze consumption trends, customer preferences, and consumer behavior (Mishra, 2019) [10]. This data can help firms make decisions regarding possible product return policies, incentives for circular behavior, and promotion of product-sharing or leasing models. In general, the use of big data and ML in the circular economy can allow more precise, timely, and data-driven processes, resulting in a more resource-effective and sustainable future. Addressing data privacy and security issues is crucial, as well as ensuring that the insights generated from these technologies are applied responsibly and morally.
1.4.3 Risk Management and ESG Compliance through Data-Driven Approaches
Tracking and Reporting of Carbon Emissions:
Many businesses use data-driven strategies to correctly measure and report their carbon emissions. To measure emissions from its supply chain, for instance, the international retail firm Walmart built a data-driven approach. Walmart can identify high-emission suppliers and work with them to lower their carbon footprint by gathering data from thousands of suppliers and using ML algorithms to analyze the information (Wang, 2020). The proof of appropriate algorithmic management in any organisation is displayed in Figure 1.2. This data-driven approach enables the organization to manage environmental risks and achieve ESG goals related to climate change. One of the biggest food and beverage corporations in the world, Nestlé, employs data-driven strategies to manage its supply chain responsibly. Nestlé collects information on supplier performance, environmental effects, and compliance with regulations using a digital supply chain platform.
Figure 1.2 ESG reporting frameworks.
Financial institutions are increasingly incorporating climate risk assessments into their risk management procedures: Climate Risk Assessment for Financial Institutions. For instance, the biggest asset manager in the world, BlackRock, has created data-driven algorithms to evaluate climate-related risks in its investment portfolios. BlackRock can identify assets vulnerable to climate risks and make wise investment decisions to limit these risks by analyzing climate data, legislative changes, and other ESG variables.
Investment businesses are using ESG data analytics for decision-making investment and businesses are using ESG data analytics for their decision-making processes. For instance, JPMorgan Asset Management assesses the ESG performance and possible risks of corporations using data-driven methods. The business acquires a greater knowledge of ESG-related risks and opportunities by combining alternative data sources, such as satellite imagery and social media sentiment research, which results in more sustainable investing strategies.
Sustainable Finance Solutions Powered by AI:
Several startups and businesses are utilizing AI-powered platforms to make sustainable finance solutions possible. For instance, True Value Labs analyzes unstructured data from diverse sources using AI algorithms to evaluate organizations’ ESG performance in real time. This data-driven strategy enables businesses and investors to make data-supported choices, improving risk management and ESG compliance.
Leading CRM providers like Salesforce use data-driven technologies to keep track of their social impact projects. Salesforce can monitor and assess the results of its social programs using data analytics, ensuring that the funds allotted to them are successful in accomplishing their intended objectives.
These instances show how data-driven methods are becoming increasingly important for risk management and maintaining ESG compliance across a range of sectors. Organizations are better equipped to understand their environmental and social implications, make wise decisions, and deepen their commitment to sustainability and ethical business practices by utilizing data and sophisticated analytics.
Ethical consideration:
To guarantee that the use of data is consistent with ethical and just practices, ethical concerns in data-driven sustainability are of the highest significance. To inform their sustainability initiatives, organizations are relying more and more on massive information, making it critical to address possible ethical issues. Data security and privacy are of particular significance since it may be possible to gather and analyze private information about people, groups, and ecosystems. To uphold people’s rights and avert potential damage, it is crucial to get informed permission and safeguard data from unauthorized access. In addition, data biases need to be recognized and eliminated to prevent perpetuating injustices or miscalculating the sustainability implications.
Building trust with stakeholders requires transparency in data gathering, analytical techniques, and decision-making procedures. Additionally, to guarantee that data-driven sustainability projects prioritize human well-being, social justice, and environmental preservation in a fair and ethical way, partnership with impacted communities and responsible data governance are crucial.
1.5 Future Trends and Challenges in ESG and Circular Economy
Initiatives related to the circular economy and ESG will face both opportunities and problems in the future. Increased investor understanding of sustainability risks and possibilities has led to a strong trend toward the inclusion of ESG factors into investment choices. Technology break-throughs like artificial intelligence and blockchain are anticipated to be crucial in improving resource efficiency, supply chain transparency, and data analytics. As more and more governments throughout the world see how urgent it is to solve environmental and social challenges, regulatory moves toward sustainable practices are expected to pick up steam.
With more businesses adopting product-as-a-service models and recycling initiatives, circular business models are also growing in popularity. However, problems still exist. Accurate ESG reporting and comparison are hampered by problems with data quality and standardization. Greenwashing is still a problem; hence accountable and open practices are required. Complex supply chains make it difficult to apply the concepts of the circular economy, necessitating efficient material tracing and management on the part of businesses. Careful thought must be given to achieving social and economic justice while pursuing sustainability objectives. Collaboration, creativity, and long-term thinking are essential for building a sustainable and circular future that can effectively navigate current obstacles and embrace future trends.
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2Blockchain Technology and Its Potential in Sustainable Finance and Investment
Neeti Misra1*, Abhilasha Chauhan2 and Nikita Siddhu1
1UIM, Uttaranchal University, Dehradun, Uttarakhand, India
2FMS, Shoolini University, Solan, Himachal Pradesh, India
Abstract
Blockchain has recently become a widely used information technology due to its efficiency as an intermediary platform. The widespread adoption of blockchain technology is revolutionizing various industries by leveraging its efficiency as an intermediary platform. This study systematically explores the multifaceted applications of blockchain in pivotal sectors such as finance, supply chain, healthcare, education, and energy consumption, thereby catalyzing the development of decentralized databases on the Internet. This research investigates the challenges and opportunities in the realm of blockchain technology, emphasizing its pivotal role in sustainable finance and investment. The current study scrutinizes the intricate relationship between blockchain and sustainable financing, illustrating how this innovative technology can reshape traditional financial models and contribute to environmentally and socially responsible investment practices. Furthermore, the study delves into the dynamic landscape of technology adoption, shedding light on the challenges encountered by diverse sectors in successfully integrating block-chain solutions. By offering a detailed elucidation of these hurdles, the research provides valuable insights into the evolving nature of blockchain implementation and lays the groundwork for formulating effective strategies to overcome obstacles. In summary, the study provides comprehensive information on the current state of blockchain technology, its applications across vital sectors, and its indispensable role in driving sustainable finance and investment. Through a meticulous examination of challenges in adoption, the research significantly contributes to the ongoing discourse surrounding the transformative potential of blockchain, which plays a key role in shaping a more resilient and sustainable future.
Keywords: Blockchain, sustainable development, sustainable finance, investment
2.1 Introduction
Innovation in various services such as transport, electricity, and water, sectors that account for the bulk of global emissions, can have a significant impact on reducing emissions. But this will require a game-changing approach, rethinking how low-carbon transitions can be achieved cost-effectively and fairly. The key features of blockchain and other distributed ledger technologies enable deep technological integration, standardization, and the possibility of new business models. Their ability to integrate with other key technologies such as IoT and artificial intelligence can have a significant impact on traditional services. Blockchain technology (BCT) can open up new areas of financing and support the promise of lowering costs for existing businesses by creating new sources. The stated goal is to increase revenue, transparency, and access to finance while reducing the cost of capital for infrastructure projects.
The integration of BCT in various fields has attracted much attention due to its transformative potential, especially in the field of finance and sustainable investment. The purpose of this work is to investigate the mul-tifaceted aspects of blockchain’s impact on sustainable financial practices using various academic partnerships.
Blockchain’s role in sustainable finance is underscored by its ability to address longstanding challenges in traditional financial systems. Naderi and Tian (2022) [1] emphasize the potential of blockchain in tokenizing green assets, offering a mechanism to fill critical gaps in green finance. The study conducted by Parmentola etal. (2022) [2] systematically reviews the environmental sustainability implications of blockchain, providing a foundational perspective within the context of sustainable development goals (SDGs). This examination of blockchain’s influence extends beyond environmental considerations to encompass broader implications for financial inclusion (Mhlanga, 2023) [3] and supply chain sustainability (Ayan et al., 2022) [4].
The motivation behind this study is a recognition of the urgency to address global environmental challenges, as highlighted by influential bodies such as the United Nations Environment Programme (UNEP, 2020) [5] and the Intergovernmental Panel on Climate Change (IPCC, 2021) [6]. The need for innovative solutions in sustainable finance is underscored by the World Bank Group (2021) [7] and the Organization for Economic Co-operation and Development (OECD, 2023) [8], as evidenced in their strategies to leverage blockchain technologies.
Moreover, the burgeoning interest and strategic considerations in various regions, as exemplified by the comprehensive “Blockchain: The India Strategy” document released by Niti Aayog (2020) [9], reflect a broader global commitment to exploring the potential of blockchain in advancing sustainable finance.
Against this background, the research aims to help understand how BCT can play a revolutionary role in sustainable finance and investment. By combining the results of several studies, this article focuses on key points in the existing literature and provides the basis for future research and practice in this field.
2.2 Literature Review
BCT has emerged as a transformative force, capturing considerable attention for its potential to reshape industries and, notably, foster environmental sustainability. In a seminal contribution, Parmentola et al. (2022) [2] conducted a systematic review that provided a comprehensive understanding of how blockchain aligns with the SDGs. Their work elucidates the intricate ways in which blockchain contributes to addressing contemporary ecological challenges, positioning it as a pivotal tool for sustainable solutions.
Expanding the discourse across industries, Ayan et al. (2022) [4] adopted a mixed-method approach to delve into the practical applications of block-chain. Their research underscores the adaptive versatility of blockchain, showcasing its role in instilling sustainability practices and optimizing supply chain management across diverse sectors. This exploration resonates with the broader theme of blockchain’s applicability across industries.
Shifting the focus to financial inclusion, Mhlanga’s study (2023) [3] adds differentiation by investigating how blockchain bridges financial gaps in Industry 4.0 era. The study positions blockchain as a catalyst for sustainable economic growth, emphasizing its potential to democratize access to financial services and foster inclusive development.
Addressing the green finance gap, Naderi and Tian’s work (2022) [1] proposes innovative solutions through the tokenization of green assets. This not only aligns financial systems with sustainable practices but also underscores blockchain’s transformative potential in shaping the future of green finance. The industry-specific lens adopted by Ata et al. (2023) [10] strengthens the argument. By investigating the impact of blockchain on the income of investment projects, this research provides tangible insights into how blockchain influences specific domains, offering a nuanced understanding of its real-world implications.
On a broader strategic level, national and global bodies have recognized blockchain’s potential for sustainable development. The India Strategy on Blockchain (Niti Aayog, 2020) [9] has an immense scope as a digital enabler for sustainable infrastructure, underscoring the imperative of integrating blockchain into sustainability strategies at both domestic and worldwide levels.
Also, the environmental conservation is amplified by the United Nations Environment Programme (UNEP, 2020) [5]. Their report emphasizes blockchain’s potential contributions as a catalyst for sustainable practices, shedding light on its role in environmental conservation efforts.
Lastly, this review underscores the transformative potential of block-chain in propelling sustainability across diverse domains. The next section will investigate deeper into the specific role of blockchain in sustainable finance and investment, unraveling its details and broader implications for the financial landscape.
2.2.1 Blockchain Technology
Blockchain, the basis of Bitcoin, has started to attract attention recently. Blockchain acts as an immutable ledger that allows transactions to occur in a distributed manner. Blockchain-based applications continue to emerge, including financial services, reputation, Internet of Things (IoT), and more. Blockchain is a tamper-proof system used to record transactions on a public or private network. Once distributed to all participants in the network, the list is permanently locked in the block. In blockchain, many functions (anonymity functions, cryptographic information, legal contracts, smart contracts, and reputation) are integrated into a distributed system. The system can manage many types of services for end users - agentless, open, consistent, traceable, and secure services at low cost but without unnecessary interference. Blockchain provides strong support for business: decentralization, security and behavior, immutability, and functions such as ideas and even actions work and good reasoning (Chen et al., 2022) [11].
Each confirmed and validated block is called a blockchain because it is linked from the beginning to the end of the chain. Instead of depending on a third party, such as a financial institution, to settle transactions, block-chain network participants use a consensus process to agree on recorded data, cryptographic hashes, and digital signatures to secure transactions.
This method is recommended to allow enough time to write to the digital file so that the metadata is not retrieved or altered. It can be defined as a software protocol that cannot work without the Internet. Peer-to-peer blockchain networks prevent a single participant or group of participants from controlling the underlying processes or systems. All network participants are equal and follow the same rules.
2.2.2 Sustainable Finance and Investment
Sustainable finance refers to the process of long-term investing in businesses and projects, including environmental, social, and governance (ESG) and the decisions to invest in financial markets. Thinking about the environment covers many areas, not only climate change and adaptation but also biodiversity conservation, pollution prevention, and circular economy. Leadership, labor relations, skills, expertise, social investment, human rights issues, etc., we can examine these in sustainable finance and investment issues. Public and private management (management standards, employee relations, salaries, etc.) play an important role in taking into account society’s energy and environmental views (Gonzalez, 2021) [12].
Sustainable finance refers to the financing of things that are environmentally friendly today (green money) and things that turn into environmentally friendly performance over time (financial change). Climate change refers to the use of private financing to reduce existing carbon emissions or other environmental impacts and for climate change transition and economic sustainability. For example, these could be investments in green manufacturing or reducing the environmental footprint of non-green technologies. Economic reforms are urgently needed to reduce greenhouse gas emissions and environmental impacts by 55% by 2030. Companies that want to be sustainable but will need to increase often need bridge financing, in other words, companies with different starting points are looking for financing for their operations next trip (Levy and Kolk, 2002) [13].
Sustainable finance means taking into account the ESG aspects of the project when choosing an investment. It aims to determine the economic value of SDGs such as reducing carbon monoxide emissions, promoting sustainability, and protecting natural resources.
This financial perspective considers the long-term impact of investment decisions on returns and the wider impact on society and the environment. It allows companies to invest in projects that improve livelihoods, protect ecosystems, and preserve natural resources for future generations. A positive environmental impact can improve personal health and increase personal investment (Thompson, 2023) [14].
Sustainable finance is financial policies, procedures, standards, and products aimed at protecting the environment. Connect financial systems to your business and people by supporting your agents as they achieve growth goals. In addition, a sustainable financial framework provides a pathway for these financial activities to ensure that investment and finance operate effectively in line with development goals (Strandberg, 2005) [15].
Environmental, social, and corporate governance is an important aspect of financial sustainability (ESG). Environmental considerations often include climate change, mitigation, and environmental issues. The word “thinking” can refer to issues such as human rights, investment in human capital, labor relations, inequality, and participation. Governance includes public and private administration. Therefore, it plays an important role in ensuring that social and environmental factors are taken into account in the decision-making process.
Therefore, financial stability management of financial disclosure has become important because investors and stakeholders want more transparency and accountability from companies and financial institutions. These regulations help investors make investment decisions regarding the safety of their investments (Chandler, 2014) [16].
These business decisions benefit customers and consumers. Sustainable financial development covers many activities. Examples of these activities include ownership, sustainable lending, green finance, impact investing, microfinance, and sustainable finance.
In addition, this approach can support and improve the competitiveness, efficiency, and success of your business now and in the future. It also helps protect and restore ecosystems and promote culture and health. Additionally, sustainable financial principles minimize environmental and social impacts by promoting good financial practices (Gann et al., 2019) [17]. These investment principles are:
It is good for growth.
Transparency and disclosure
Stakeholder engagement
Responsible investment and lending
Corporate responsibility
Building a more secure future requires a multidisciplinary approach that includes finance.
The financial sector has great power in financing and raising awareness of sustainability issues, supporting alternative energy research and development, and supporting companies that work with the principles of justice and common sense. Sustainable finance is defined as investment decisions that take into account the ESG aspects of a business or project.
Environmental factors such as reducing pollution and using sustainable resources. Community topics include human and animal rights, as well as consumer protection and various forms of employment.
Management process refers to the management, employee relations, and compensation of public and private organizations. Sustainable finance involves investment decisions that consider ESG issues as well as financial returns, also known as “green finance” (Boffo and Patalano, 2020) [18].
Sustainable finance involves investment decisions that consider the ESG aspects of a business or project. Sustainability is here, and over time investors have become increasingly interested in ESG solutions. ESG also includes human rights. Environmental pollution, health, and social problems. End poverty has equal rights in the workplace. Strictly comply with local, state, federal, and international regulations. Many countries are implementing new sustainable finance strategies and sustainable finance development projects (Krambia-Kapardis et al., 2023) [19]. Environmental considerations include mitigating climate impacts and using sustainable resources. Community topics include human and animal rights, as well as consumer protection and various forms of employment. The management process refers to management, employee relations, and rewards in public and private organizations (Dhaliwal and Malik, 2021) [20].
Community development is investing in people, eliminating problems, and ensuring justice, security, dignity, and respect for all citizens. Education, care, job creation, health and livelihoods, and safe communities contribute to health. Today, companies are more aware of the importance of investing in society and the indirect benefits of their actions for its employees and for the public itself. From an organizational perspective, companies not only view ESG as “a decision” but also make such decisions in a broader context (El Khoury et al., 2023) [21].
A sustainable business definition depends on business leaders making decisions that benefit people, the environment, and the economy. Business leaders must have business knowledge, first, responsibility for profit, second, responsibility for success, and third, environmental responsibility. Business leaders must be ethical leaders whose results support our sustainable business bottom line. Virtue honesty gives business leaders integrity and helps them make good decisions about factories, people, and profits. Leaders must apply ethical rules in their daily lives that will help them make decisions not only for the benefit of the business organization but also for current and future pressing needs (Lenka and Kar, 2021) [22].
Value investing includes a variety of activities, from investing in green projects to investing in companies with proven value, such as quality of social inclusion and good governance with women on boards.
Sustainable finance has become an important concept in cross-cutting areas: financial goals and sustainability. Sustainability financing should include all activities and activities that contribute to financial stability and growth (Kumar et al., 2022) [23].
The focus points in the green investment process of the development of the international economy are defined as follows: 1) increased demand from government and commercial enterprises, commercial enterprises, and families to attract stable capital to increase the levels of local and international competitiveness markets; 2) national economy. Significant changes in ecology lead to the diversification of financial instruments; 3) The differentiation of the business model of the world financial market and the emergence of new organizations; 4) Geographical and instrumental asymmetries and depth (Ilnytskyy and Stoliarchuk, 2023) [24].
There are many different types of fixed income depending on the definition of fixed income and fixed investment (Cunha et al., 2021) [25]. It includes:
2.2.2.1 Sustainable Foreign Direct Investment (SFDI)
SFDI generally refers to cross-border investment from developed to developing countries for sustainability purposes. SFDI is seen as a way to achieve the goals set by the United Nations 2030 Agenda for Sustainable Development. Sustainable development is important in the development of foreign direct investment, which will support job creation, increase productivity, and improve people’s living standards. Lawmakers will concentrate on sustainable development to attract foreign direct investment (Sheikh et al., 2022) [26].
2.2.2.2 Impact Investing
Impact investing is designed to generate good returns and have a healthy impact on society or the environment. Impact investors consider a company’s ESG performance and sustainability information when making investment decisions. Impact investing helps people and the environment without creating financial impact. It seeks to solve global problems in energy, water, sanitation, food, health, and education by exploring new solutions (Barber et al., 2021) [27].
2.2.2.3 Socially Responsible Investment (SRI)
SRIs make investment choices based on social or ethical principles. Being socially responsible may include avoiding investments that are harmful to society, such as the manufacture of weapons or cigarettes, and seeking companies committed to social justice. Socially responsible investing (SRI) is defined as a strategy that selects investors based on growth capital with ESG responsibility and financing. Companies and financial institutions can expand the investor base of responsible products by promoting financial products that increase the personal value of investors while generating satisfying income (Bollazzi and Risalvato, 2018) [28].
