Sinopsis
"By addressing the implications of blockchain and generative AI, the book encourages critical engagement with ethical and sustainability issues in finance, preparing students for future challenges. Society at large stands to gain from the promotion of financial inclusion and sustainable practices highlighted in the book, as well as increased consumer education on the benefits and risks of these technologies. Ultimately, this work contributes to building trust in financial systems, empowering individuals,and aligning financial practices with global sustainability goals, creating a more equitable and informed society"-- Provided by publisher.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca de los autores
Mohammad Irfan is presently working as a Professor at School of Business and Commerce, Chandigarh University, Lucknow, Unnao, India. Dr. Irfan has done his Ph.D. from the Central University of Haryana. He has MBA (Finance), M.Com (Account and Law), and MA (Economics). He has qualified UGC-JRF/SRF/NET in Management and Commerce. Dr. Irfan certified NSEs (NCFM) and BSEs certification. He has experience of more than eighteen years in the area of SAPM, Integration of AI/ML in Finance, Blockchain, Cryptocurrency, Financial Engineering, Fintech, Green Finance, and Alternative Finance. He has to his credit more than 87+ Scopus-indexed articles, including The Journal of Economic Cooperation and Development (Q2), International Journal of Business Excellence (IJBEX), International Journal of Economics and Management (IJEM), Montenegrin Journal of Economics (Q2), Cogent Business & Management (Taylor & Francis) (Q2), Indian Journal of Finance (IJF), and Journal of Islamic Monetary Economics and Finance (JIMF). His citations reached 619+ along with 13 H-index. Dr. Irfan has published 11 books in Springer, Bentham Sciences, Apple Academic Press (CRC Press, Taylor & Francis, and IGI Global Publication (Scopus indexed).
Dr. Gilney Figueira Zebende , He is currently a full professor at the State University of Feira de Santana. He has experience in Physics, with an emphasis on Condensed Matter Physics, working mainly on the following topics: dfa, long-range correlation, dcca, dcca cross-correlation coefficient, rho_dcca coefficient and quantum finance. How AI and Eduction coming togather to resolve the current generation need abd challenges. Dr. Gilney has citaions on his research work 3114+
"Sobre este título" puede pertenecer a otra edición de este libro.
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Paperback. Condición: new. Paperback. Generative AI emerges as a powerful tool in the financial sector, offering new insights and capabilities that transform decision-making processes. By synthesizing complex datasets, generative models can uncover patterns, simulate market scenarios, and generate forecasts with greater speed and precision than traditional methods. These models support a range of applications, enabling institutions to make more informed, data-driven decisions. As generative AI evolves, it presents both opportunities and challenges, calling for a careful balance between innovation, transparency, and regulatory compliance in financial operations. Generative AI Insights for Financial Decision Making explores the implications of blockchain and generative AI in the finance sector. It examines best practices for optimizing operations and developing innovative financial products that meet evolving consumer demands. This book covers topics such as financial security, blockchain, and payment systems, and is a useful resource for engineers, business owners, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798337312514
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Taschenbuch. Condición: Neu. Generative AI Insights for Financial Decision Making | Mohammad Irfan (u. a.) | Taschenbuch | Englisch | 2025 | IGI Global | EAN 9798337312514 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 133652132
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