Big Data And Artificial Intelligence In Digital Finance
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Big Data And Artificial Intelligence In Digital Finance
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Author : John Soldatos
language : en
Publisher: Springer Nature
Release Date : 2022-04-29
Big Data And Artificial Intelligence In Digital Finance written by John Soldatos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-29 with Technology & Engineering categories.
This open access book presents how cutting-edge digital technologies like Big Data, Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTech, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also describes some more the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance.
Artificial Intelligence For Sustainable Finance And Sustainable Technology
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Author : Abdalmuttaleb M. A. Musleh Al-Sartawi
language : en
Publisher: Springer Nature
Release Date : 2022-01-01
Artificial Intelligence For Sustainable Finance And Sustainable Technology written by Abdalmuttaleb M. A. Musleh Al-Sartawi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Technology & Engineering categories.
This book shows latest research on artificial intelligence for sustainable technology. ICGER 2021 was organized by the Accounting, Finance and Banking Department at Ahlia University, Bahrain, and was conducted on the 15th and 16th of September. The strategic partners included the University of Jordan, the Bahrain Economists Society, the Association of Chartered Certified Accountants: ACCA, Al-Barka Banking Group and the International Computer Auditing Education Association: ICAEA . The theme of the ICGER 2021 centered around artificial intelligence for sustainable finance and sustainable technology. Accordingly, the papers presented at the conference provided a holistic view of sustainable finance, sustainability, AI, financial technology, cybersecurity, blockchain, CSR, and governance. This book, unlike ever before, brings together intelligence applications of new technologies and the sustainability requirements in the era of the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI applications and financial technologies to develop future strategies and to achieve sustainable development goals.
The Impact Of Ai Innovation On Financial Sectors In The Era Of Industry 5 0
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Author : Irfan, Mohammad
language : en
Publisher: IGI Global
Release Date : 2023-09-05
The Impact Of Ai Innovation On Financial Sectors In The Era Of Industry 5 0 written by Irfan, Mohammad and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-05 with Business & Economics categories.
In the dynamic and ever-changing financial landscape, the seamless integration of artificial intelligence (AI) and machine learning (ML) has presented unprecedented challenges for the banking and finance industry. As we embrace the era of Industry 5.0, financial institutions find themselves confronted with intricate decisions pertaining to investments, macroeconomic analysis, and credit evaluation, necessitating innovative technologies to navigate this complexity. Additionally, the mounting volume of financial transactions calls for efficient data processing and analysis. Considering these pressing concerns, scholars, academicians, and industry practitioners are eagerly seeking comprehensive insights into the transformative potential of AI and ML, specifically in bolstering resilience, fostering sustainable development, and adopting human-centric approaches within the financial sector. Offering a compelling solution to these critical challenges, The Impact of AI Innovation on Financial Sectors in the Era of Industry 5.0, edited by esteemed scholars Mohammad Irfan, Mohammed Elmogy, M. Shabri Abd. Majid, and Shaker El-Sappagh, embark on an in-depth exploration of the multifaceted functions and applications of AI and ML algorithms in the realm of finance. With a keen focus on Industry 5.0 principles such as resilience, human centricity, and sustainable development, this comprehensive compendium presents a collection of groundbreaking research papers that unveil the remarkable potential of AI/ML technologies in revolutionizing the financial services industry. By catering to a diverse audience comprising researchers, academicians, industrialists, investors, and regulatory bodies, this book actively invites contributions from industry practitioners and scholars, facilitating ongoing discussions on the efficacy of ML algorithms in efficiently processing vast financial data. As the financial landscape charts an ambitious course into Industry 5.0, the book emerges as an indispensable resource, empowering the industry with transformative advancements that will indelibly shape the future of finance.
Big Data
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Author : Kiran Sood
language : en
Publisher: Emerald Group Publishing
Release Date : 2022-07-19
Big Data written by Kiran Sood and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-19 with Business & Economics categories.
Striking a balance between the technical characteristics of the subject and the practical aspects of decision making, spanning from fraud analytics in claims management, to customer analytics, to risk analytics in solvency, the comprehensive coverage presented makes Big Data an invaluable resource for any insurance professional.
The Rise Of Digital Finance
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Author : Valeria Stefanelli
language : en
Publisher: FrancoAngeli
Release Date : 2023-02-01T14:38:00+01:00
The Rise Of Digital Finance written by Valeria Stefanelli and has been published by FrancoAngeli this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-01T14:38:00+01:00 with Business & Economics categories.
365.1287
Sustainable Finance In Europe
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Author : Danny Busch
language : en
Publisher: Springer Nature
Release Date : 2024-05-18
Sustainable Finance In Europe written by Danny Busch and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-18 with Business & Economics categories.
This second edition brings together the views of expert academics and practitioners on the latest regulatory developments in sustainable finance in Europe and includes 5 new chapters on sustainable remuneration, reporting, lending, green monetary policy and ESG. The volume includes a wide range of cutting-edge issues, which relate to three main themes along which the volume is structured: (1) corporate governance; (2) monetary policy and financial stability ; and (3) financial markets. With individual contributions deploying different methods of analysis, including theoretical contributions on the status quo of macro-financial research as well as law and economics approaches, the collection encourages interdisciplinary readership and will appeal to those researching capital markets law, European financial law, and sustainable finance, as well as practitioners within the finance industry.
Artificial Intelligence Fintech And Financial Inclusion
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Author : Rajat Gera
language : en
Publisher: CRC Press
Release Date : 2023-12-29
Artificial Intelligence Fintech And Financial Inclusion written by Rajat Gera and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-29 with Technology & Engineering categories.
This book covers big data, machine learning, and artificial intelligence-related technologies and how these technologies can enable the design, development, and delivery of customer-focused financial services to both corporate and retail customers, as well as how to extend the benefits to the financially excluded sections of society. Artificial Intelligence, Fintech, and Financial Inclusion describes the applications of big data and its tools such as artificial intelligence and machine learning in products and services, marketing, risk management, and business operations. It also discusses the nature, sources, forms, and tools of big data and its potential applications in many industries for competitive advantage. The primary audience for the book includes practitioners, researchers, experts, graduate students, engineers, business leaders, and analysts researching contemporary issues in the area.
Green Digital Finance And Sustainable Development Goals
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Author : Farhad Taghizadeh-Hesary
language : en
Publisher: Springer Nature
Release Date : 2022-07-01
Green Digital Finance And Sustainable Development Goals written by Farhad Taghizadeh-Hesary and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-01 with Business & Economics categories.
This book aims to fill the literature gap on digital instruments and FinTech in enhancing green finance. Technological innovation can increase transparency, accountability, and speed, decentralize the financial system, improve risk management, increase competition, lower costs, improve efficiency, increase cross-sectoral collaboration and integration, and scale up green finance. Artificial intelligence (AI), distributed ledger technologies (DLT) or blockchain, peer-to-peer lending platforms, big data, Internet-based and mobile-based payment platforms, Internet of Things (IoT), matchmaking platforms including crowdlending, tokenizing green assets are potential means to scale up the green finance for achieving the SDGs. The COVID-19 pandemic, the economic downturns, and the uncertainties shrank the new investments in renewable energy projects globally. Low investment in renewable energy projects could threaten the expansion of green energy needed to provide energy security and meet SDG7 and SDG13. Investments in renewable energy projects are scarce because of several risks and a low rate of return. Although several new green financing solutions such as green bonds, green banks, green credit guarantee, carbon taxation, carbon trade, village funds, and community trust funds have been established in different countries, these are insufficient, and alternative ways to finance projects are required. The book provides several high-quality studies on utilizing digitalization, FinTech, financial innovations, and other new technologies to fill the finance gap of green projects to meet the SDG goals. The chapters are written by scholars in diverse countries and regions and include practical policy recommendations.
The 2021 International Conference On Machine Learning And Big Data Analytics For Iot Security And Privacy
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Author : John Macintyre
language : en
Publisher: Springer Nature
Release Date : 2021-10-27
The 2021 International Conference On Machine Learning And Big Data Analytics For Iot Security And Privacy written by John Macintyre and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-27 with Computers categories.
This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.
Proceedings Of The 5th International Conference On Economic Management And Big Data Application Icembda 2024
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Author : Kun Zhang
language : en
Publisher: Springer Nature
Release Date : 2024-12-29
Proceedings Of The 5th International Conference On Economic Management And Big Data Application Icembda 2024 written by Kun Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-29 with Business & Economics categories.
This is an open access book. The 5th International Conference on Economic Management and Big Data Applications (ICEMBDA 2024) is scheduled to be held in Tianjin, China on October 25–27, 2024. The 5th International Conference on Economic Management and Big Data Application (ICEMBDA 2024) is an essential forum for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in the fields of economic management and big data analytics. Scheduled to be held in an era marked by rapidly evolving digital technologies, ICEMBDA 2024 aims to bridge the gap between big data technologies and their practical implementation in economic management. Background The integration of big data analytics into economic management has revolutionized decision-making processes by enabling more precise, evidence-based strategies that potentially lead to superior outcomes. As big data continues to grow in volume, variety, and velocity, the necessity for its application in economic strategies and policies has never been more critical. ICEMBDA 2024 addresses this urgency, acting as a pivotal platform for academic and industry professionals to synergize knowledge and foster advancements. Conference Themes ICEMBDA 2024 will center around a wide range of themes pertinent to the intersection of economics, management, and big data: Big Data Analytics and Economic Forecasting - Utilizing big data in predictive analytics to forecast economic trends and inform policy making. Data-Driven Decision Making in Business and Economics - Methods and technologies that support data-driven strategies in businesses and economic institutions. Ethics and Privacy in Big Data - Addressing the ethical considerations and privacy concerns arising from extensive big data utilization in economic management. Technological Innovations in Big Data - Exploring advancements in data processing, AI, and machine learning that enhance economic data analysis. Impact of Big Data on Economic Policy and Management - Examining how big data has transformed public and private sector economics, focusing on efficiency, accuracy, and compliance. Case Studies on Big Data Applications in Various Economic Sectors - Success stories and lessons learned from applying big data solutions across different branches of economics.