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.

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.

This comprehensive volume delves deep into the diverse applications and implications of generative AI across accounting, finance, economics, business, and management, providing readers with a holistic understanding of this rapidly evolving landscape.

Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes provides a comprehensive guide to ethically harnessing generative AI systems to reshape financial management. Generative AI is a key theme across the accounting and finance sectors to drive significant optimizations leading to sustainability. Across 22 chapters, leading researchers supply innovative applications of large language models across the economic realm. Through detailed frameworks, real-world case studies, and governance recommendations, this book highlights applied research for generative AI in finance functions. Several chapters demonstrate how data-driven insights from AI systems can optimize complex financial processes to reduce resource usage, lower costs, and drive positive environmental impact over the long term. In addition, chapters on AI-enabled risk assessment, fraud analytics, and regulatory technology highlight applied research for generative AI in finance. The book also explores emerging applications like leveraging blockchain and metaverse interfaces to create generative AI models that can revolutionize areas from carbon credit trading to virtual audits. Overall, with in-depth applied research at the nexus of sustainability and optimization enabled by data science and generative AI, the book offers a compilation of best practices in leveraging AI for optimal, ethical, and future-oriented financial management.

Audience

The audience for this book is quite diverse, ranging from financial and accounting experts across banking, insurance, consultancies, regulatory agencies, and corporations seeking to enhance productivity and efficiency; business leaders want to implement ethical and compliant AI practices; researchers exploring the domain of AI and finance.

This comprehensive volume delves deep into the diverse applications and implications of generative AI across accounting, finance, economics, business, and management, providing readers with a holistic understanding of this rapidly evolving landscape.

Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes provides a comprehensive guide to ethically harnessing generative AI systems to reshape financial management. Generative AI is a key theme across the accounting and finance sectors to drive significant optimizations leading to sustainability. Across 22 chapters, leading researchers supply innovative applications of large language models across the economic realm. Through detailed frameworks, real-world case studies, and governance recommendations, this book highlights applied research for generative AI in finance functions. Several chapters demonstrate how data-driven insights from AI systems can optimize complex financial processes to reduce resource usage, lower costs, and drive positive environmental impact over the long term. In addition, chapters on AI-enabled risk assessment, fraud analytics, and regulatory technology highlight applied research for generative AI in finance. The book also explores emerging applications like leveraging blockchain and metaverse interfaces to create generative AI models that can revolutionize areas from carbon credit trading to virtual audits. Overall, with in-depth applied research at the nexus of sustainability and optimization enabled by data science and generative AI, the book offers a compilation of best practices in leveraging AI for optimal, ethical, and future-oriented financial management.

Audience

The audience for this book is quite diverse, ranging from financial and accounting experts across banking, insurance, consultancies, regulatory agencies, and corporations seeking to enhance productivity and efficiency; business leaders want to implement ethical and compliant AI practices; researchers exploring the domain of AI and finance.

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.

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.

This comprehensive volume delves deep into the diverse applications and implications of generative AI across accounting, finance, economics, business, and management, providing readers with a holistic understanding of this rapidly evolving landscape.

Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes provides a comprehensive guide to ethically harnessing generative AI systems to reshape financial management. Generative AI is a key theme across the accounting and finance sectors to drive significant optimizations leading to sustainability. Across 22 chapters, leading researchers supply innovative applications of large language models across the economic realm. Through detailed frameworks, real-world case studies, and governance recommendations, this book highlights applied research for generative AI in finance functions. Several chapters demonstrate how data-driven insights from AI systems can optimize complex financial processes to reduce resource usage, lower costs, and drive positive environmental impact over the long term. In addition, chapters on AI-enabled risk assessment, fraud analytics, and regulatory technology highlight applied research for generative AI in finance. The book also explores emerging applications like leveraging blockchain and metaverse interfaces to create generative AI models that can revolutionize areas from carbon credit trading to virtual audits. Overall, with in-depth applied research at the nexus of sustainability and optimization enabled by data science and generative AI, the book offers a compilation of best practices in leveraging AI for optimal, ethical, and future-oriented financial management.

Audience

The audience for this book is quite diverse, ranging from financial and accounting experts across banking, insurance, consultancies, regulatory agencies, and corporations seeking to enhance productivity and efficiency; business leaders want to implement ethical and compliant AI practices; researchers exploring the domain of AI and finance.

This comprehensive volume delves deep into the diverse applications and implications of generative AI across accounting, finance, economics, business, and management, providing readers with a holistic understanding of this rapidly evolving landscape.

Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes provides a comprehensive guide to ethically harnessing generative AI systems to reshape financial management. Generative AI is a key theme across the accounting and finance sectors to drive significant optimizations leading to sustainability. Across 22 chapters, leading researchers supply innovative applications of large language models across the economic realm. Through detailed frameworks, real-world case studies, and governance recommendations, this book highlights applied research for generative AI in finance functions. Several chapters demonstrate how data-driven insights from AI systems can optimize complex financial processes to reduce resource usage, lower costs, and drive positive environmental impact over the long term. In addition, chapters on AI-enabled risk assessment, fraud analytics, and regulatory technology highlight applied research for generative AI in finance. The book also explores emerging applications like leveraging blockchain and metaverse interfaces to create generative AI models that can revolutionize areas from carbon credit trading to virtual audits. Overall, with in-depth applied research at the nexus of sustainability and optimization enabled by data science and generative AI, the book offers a compilation of best practices in leveraging AI for optimal, ethical, and future-oriented financial management.

Audience

The audience for this book is quite diverse, ranging from financial and accounting experts across banking, insurance, consultancies, regulatory agencies, and corporations seeking to enhance productivity and efficiency; business leaders want to implement ethical and compliant AI practices; researchers exploring the domain of AI and finance.