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  • BSZ  (5)
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  • English  (5)
  • Italian
  • 2020-2024  (5)
  • 1990-1994
  • 2023  (5)
  • Walker, Thomas  (3)
  • Gupta, Deepak  (2)
  • Cham : Springer International Publishing  (5)
  • Cham : Springer International Publishing AG  (1)
  • Cambridge : Polity Press
  • Aufsatzsammlung  (3)
  • Artificial intelligence.  (2)
  • Artificial intelligence  (1)
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  • English  (5)
  • Italian
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  • 2020-2024  (5)
  • 1990-1994
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  • 1
    ISBN: 9783031238116
    Language: English
    Pages: 1 Online-Ressource (XXVII, 367 p. 49 illus., 43 illus. in color.)
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Power resources. ; Environmental economics. ; Financial risk management. ; Sustainability. ; Water. ; Hydrology. ; Energy policy. ; Energy and state. ; Risk management ; Water risk management ; Modeling Financial Water Risk ; the quantification of financial water risk ; Risk-return techniques ; Aufsatzsammlung
    Abstract: Chapter 1: Introduction -- Part I: Framework of Financial Water Risk -- Chapter 2: Drivers of water risk and their interaction -- Chapter 3: Water risk and climate change -- Chapter 4: Interaction effects of water risk in finance and society -- Chapter 5: Opportunities from water risk -- Part II: Modeling Financial Water Risk -- Chapter 6: Presentation of specific water risk models (different chapters) -- Chapter 7: Financial water risk and accounting/risk reporting -- Chapter 8: Water risk stress testing -- Chapter 9: Modelling financial water risk approaches using neural networks, artificial intelligence, and other advanced methods -- Part III: Managing Financial Water Risk -- Chapter 10: Financial water risk and the use of data science (e.g., advances in high-resolution geo-mapping) -- Chapter 11: Water risk governance of companies and countries -- Chapter 12: Water risk insurance -- Chapter 13: Water risk derivatives -- Chapter 14: Water risk management of investment portfolios -- Chapter 15: Directions in water risk regulations -- Chapter 16: Conclusions.
    Abstract: This book sheds light on the topic of financial water risk by examining the modeling challenges associated with physical, regulatory, and reputational water risk in finance. It explores various approaches to operationalize water risk from a financial analysis, investment management, and climate science perspective. The analysis of tools to assess water risk provides the basis for the development of appropriate risk-return management techniques in finance and beyond. This book provides new insights by focusing on financial water threats and their related opportunities. It will be of interest to both academics and practitioners who work at the interface of finance, economics, nature, and society. Dieter Gramlich is a Professor at DHBW – Baden-Wuerttemberg Cooperative State University in Heidenheim, Germany, where he serves as Head of the Banking Department. He previously studied at the University of Mannheim and was an interim professor and Chair of Banking & Finance at the University of Halle. His research focuses on sustainable finance. Thomas Walker is a Professor of Finance and Concordia University Research Chair in Emerging Risk Management at Concordia University, Montreal, Canada. Prior to academia, he worked in the German consulting and industrial sector at Mercedes Benz, Utility Consultants International, Lahmeyer International, Telenet, and KPMG Peat Marwick. Maya Michaeli works as a Research Associate in the Department of Finance at Concordia University, Montreal. She has a natural passion for financial markets and the future of sustainable investments and has participated in numerous research projects in those areas. Charlotte Esme Frank completed her Bachelor’s degree in the Humanities at Carleton University, Ottawa. She holds an MA in English Literature and Creative Writing from Concordia University, Montreal, where she is a Research Associate at the John Molson School of Business. She is currently completing a PhD in English literature at McGill University.
    URL: Cover
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  • 2
    ISBN: 9783031230691
    Language: English
    Pages: 1 Online-Ressource (XXX, 378 p. 52 illus., 38 illus. in color.)
    Series Statement: Palgrave Studies in Financial Services Technology
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als The fintech disruption
    RVK:
    RVK:
    Keywords: Financial engineering. ; Financial services industry. ; Artificial intelligence ; Cloud computing ; Cryptocurrencies ; Blockchain ; Fintech ; Banking ; the Internet of Things ; ABCDI ; the opportunities and risks Fintech ; Aufsatzsammlung
    Abstract: INTRODUCTION -- Chapter 1 Fintech and Banking: An Overview. SECTION I: FINANCIAL TECHNOLOGIES AND THEIR EFFECTS ON THE BANKING INDUSTRY -- Chapter 2 Centralized and Decentralized Finance: Coexistence or Convergence? -- Chapter 3 Fintech and the Digital Transformation of the Banking Landscape -- Chapter 4 Shifting paradigms in banking: How new service concepts and formats enhance the value of financial services -- Chapter 5 Competitors and Partners at the Same Time: On the Role of Fintech Companies in the Latvian Financial Market -- Chapter 6 Non-Fungible Tokens -- SECTION II: CHALLENGES, OPPORTUNITIES, AND REGULATIONS REGARDING FINTECH IN THE BANKING INDUSTRY -- Chapter 7 Open Banking: Opportunities and Risks -- Chapter 8 The Rise of Financial Services Ecosystems: Towards Open Banking Platforms -- Chapter 9 The Crypto-assets Market in the United Kingdom: Regulatory and Legal Challenges -- Chapter 10 A Preliminary Comparison of Two Ecosystems: Fintech Opportunities and Challenges for Financial Inclusion -- Chapter 11 Investigating Variables that Increase the Desire and Loyalty to Utilize Fintech After the COVID-19 Lockdown: A New Normal Habit -- SECTION III: EVIDENCE FROM AROUND THE WORLD -- Chapter 12 Fintech and Financial Inclusion in Developing Countries -- Chapter 13 The Cash Holdings of Fintechs and SMEs: Evidence from OECD Countries -- Chapter 14 Fintech Companies in Brazil: Assessing Their Effects on Competition in the Brazilian Financial System from 2018 to 2020.
    Abstract: This book provides both practice-oriented and academic insights into the disruptive power of fintech for the banking industry. It explores (1) whether and how the banking industry can use newly emerging technologies in the financial sphere to its advantage while managing any associated risks, (2) how these technologies affect traditional banking service formats as well as the pricing of these services, and (3) whether the emergence of fintech in the banking industry calls for a rethinking of existing banking regulations such as the Basel Accords as well as country-specific regulations. Prior publications in this area typically examine both current applications of fintech in the banking industry, as well as its future prospects, by analyzing actual cases or exploring the impact of a single emerging technology on the banking industry. They often ignore the interdependence between emerging technologies and overlook the connection between fintech as a whole and the future of the banking industry. This book addresses this gap by providing a comprehensive overview of various fintech applications and by analyzing what they mean for the future of banking. Given the potentially disruptive power of fintech, the book will focus on the challenges banking supervisors are likely to encounter as a result of fintech’s continual ascent. It will thus encourage readers to think about and explore how to find a balance between the beneficial aspects of fintech and the challenges it creates in terms of supervision, regulation, and risk management. Thomas Walker is Professor of Finance and Concordia University Research Chair in Emerging Risk Management at Concordia University, Montreal, Canada. Prior to academia, he worked for several years in the German consulting and industrial sector at Mercedes Benz, Utility Consultants International, Lahmeyer International, Telenet, and KPMG Peat Marwick. Elaheh Nikbakht currently serves as Data Management and Reporting Administrator in the Entity Services Department of Maples Group. In addition, she works as a Research Assistant for the Emerging Risks Information Centre and the Department of Finance at Concordia University. She holds an MBA and an MSc in Finance from Concordia University. Maher Kooli is a Full Professor of Finance at the School of Management (ESG), Université du Québec à Montréal (UQAM) and head of the Finance Department. He is the Caisse de Depot et Placement de Québec (CDPQ) research chair-holder in portfolio management, founder of the trading room at ESG UQAM, and Autorite des marches financiers (AMF) and Finance Montreal research co-chair-holder in fintech at ESG UQAM.
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  • 3
    ISBN: 9783031182921
    Language: English
    Pages: 1 Online-Ressource(X, 181 p. 61 illus., 46 illus. in color.)
    Edition: 1st ed. 2023.
    Series Statement: Studies in Computational Intelligence 1072
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Artificial intelligence.
    Abstract: Explainable Artificial Intelligence: Concepts and Current Progression -- Explainable Artificial Intelligence (XAI): Understanding and Future Perspectives -- Explainable Artificial Intelligence (XAI): Conception, Visualization and Assessment approaches towards amenable XAI -- Explainable AI (XAI): A Survey of Current and Future Opportunities -- Recent Challenges on Edge AI with its application: A Brief Introduction -- Explainable Artificial Intelligence in Health Care: How XAI Improves User Trust in High-Risk Decisions -- Role of Explainable Edge AI to Resolve Real Time Problem -- Explainable Data Fusion on Edge: Challenges and Opportunities -- Trust Model Based Data Fusion in Explainable Artificial Intelligence for Edge Computing Using Secure Sequential Discriminant Auto Encoder with Lightweight Optimization Algorithm -- A Deep Learning Based Target Coverage Protocol for Edge Computing Enabled Wireless Sensor Networks.
    Abstract: This book presents explainability in edge AI, an amalgamation of edge computing and AI. The issues of transparency, fairness, accountability, explainability, interpretability, data-fusion, and comprehensibility that are significant for edge AI are being addressed in this book through explainable models and techniques. The concept of explainable edge AI is new in front of the academic and research community, and consequently, it will undoubtedly explore multiple research dimensions. The book presents the concept of explainability in edge AI which is the amalgamation of edge computing and AI. In the futuristic computing scenario, the goal of explainable edge AI will be to execute the AI tasks and produce explainable results at the edge. First, this book explains the fundamental concepts of explainable artificial intelligence (XAI), then it describes the concept of explainable edge AI, and finally, it elaborates on the technicalities of explainability in edge AI. Owing to the quick transition in the current computing scenario and integration with the latest AI-based technologies, it is significant to facilitate people-centric computing through explainable edge AI. Explainable edge AI will facilitate enhanced prediction accuracy with the comprehensible decision and traceability of actions performed at the edge and have a significant impact on futuristic computing scenarios. This book is highly relevant to graduate/postgraduate students, academicians, researchers, engineers, professionals, and other personnel working in artificial intelligence, machine learning, and intelligent systems.
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  • 4
    ISBN: 9783031295294 , 3031295293
    Language: English
    Pages: 1 Online-Ressource (XVII, 183 Seiten) , 15 illus., 8 illus. in color.
    Edition: 1st ed. 2023
    Parallel Title: Erscheint auch als Environmental Migration in the Face of Emerging Risks
    DDC: 304.2
    Keywords: Human geography ; Emigration and immigration ; Environmental sciences Social aspects ; Demography ; Population ; Human Geography ; Human Migration ; Environmental Social Sciences ; Population and Demography ; Aufsatzsammlung ; Aufsatzsammlung
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 5
    ISBN: 9783031380365
    Language: English
    Pages: 1 Online-Ressource(XIV, 233 p.)
    Edition: 1st ed. 2023.
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    Keywords: Computational intelligence. ; Multimedia systems. ; Medical informatics. ; Machine learning. ; Artificial intelligence.
    Abstract: Foreword -- Preface -- Acknowledgement -- Table of Contents -- Chapter 1: -- Automatic Fetal Motion Detection from Trajectory of US Videos Based on YOLOv5 and LSTM -- Chapter 2: -- Explainable Machine Learning (XML) for Multimedia-based Healthcare Systems: Opportunities, Challenges, Ethical and Future Prospects -- Chapter 3: -- Ensemble deep learning architectures in bone cancer detection based on Medical Diagnosis in Explainable Artificial Intelligence -- Chapter 4: -- Digital dermatitis disease classification utilizing visual feature extraction and various machine learning techniques by explainable AI -- Chapter 5: -- Explainable Machine Learning in Healthcare -- Chapter 6: -- Explainable Artificial Intelligence with Scaling Techniques to Classify Breast Cancer Images -- Chapter 7: -- A Novel Approach of COVID -19 Estimation Using GIS and Kmeans Clustering: A Case of GEOAI -- Chapter 8: -- A Brief Review of Explainable Artificial Intelligence Reviews and Methods -- Chapter 9: -- Systematic Literature Review In Using Big Data Analytics And XAI Applications In Medical -- Chapter 10: -- Using Explainable Artificial Intelligence In Drug Discovery: A Theoretical Research -- Chapter 11: -- Application of Interpretable Artificial Intelligence enabled Cognitive Internet of Things for COVID-19 Pandemics -- Chapter 12: -- Remote Photoplethysmography: Digital Disruption in Health Vital Acquisition.
    Abstract: This book covers the latest research studies regarding Explainable Machine Learning used in multimedia-based healthcare applications. In this context, the content includes not only introductions for applied research efforts but also theoretical touches and discussions targeting open problems as well as future insights. In detail, a comprehensive topic coverage is ensured by focusing on remarkable healthcare problems solved with Artificial Intelligence. Because today’s conditions in medical data processing are often associated with multimedia, the book considers research studies with especially multimedia data processing.
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