Gupta D. Computational Intelligence for Autonomous Finance 2025

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Gupta D. Computational Intelligence for Autonomous Finance 2025

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Added: 2025-03-10 23:39:10

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Textbook in PDF format The book serves as an essential guide and a deep dive into the intersection of Artificial Intelligence (AI) and finance, providing readers with a thorough understanding of the current state, challenges, and future possibilities of autonomous financial systems. In the rapidly evolving domain of autonomous finance, the convergence of Computational Intelligence techniques (CI) and financial technologies has paved the way for a new era of financial services. This transformation is driven by the integration of Artificial Intelligence (AI), Machine Learning (ML), blockchain, and big data analytics into financial systems, leading to the development of more responsive, efficient, and personalized financial products and services. Computational Intelligence for Autonomous Finance delves into the heart of this technological revolution, offering a comprehensive exploration of the theoretical foundations, practical applications, and future prospects of Computational Intelligence in the financial sector. The backbone of autonomous finance is a complex, interconnected ecosystem that leverages Computational Intelligence to automate decision-making processes, optimize financial operations, and enhance customer experiences. The book introduces the concept of an Intelligent Autonomous Financial Network (IAFN), which integrates various Computational Intelligence techniques with cutting-edge financial technologies to create a self-organizing, adaptive, and scalable financial system. The IAFN framework facilitates seamless interactions between diverse financial entities, enabling the provision of innovative financial services such as automated trading, real-time risk management, personalized financial planning, and fraud detection. The book meticulously analyzes the key challenges including data security and privacy concerns, algorithmic biases, regulatory compliance, and the need for interoperable standards. It also presents state-of-the-art solutions and best practices for overcoming these challenges, emphasizing the importance of ethical AI, robust data protection mechanisms, transparent algorithms, and collaborative regulatory frameworks. It discusses emerging trends such as quantum computing, edge computing, and decentralized finance (DeFi), highlighting their potential to further transform the financial landscape. The book also addresses the societal implications of autonomous finance, including its impact on employment, wealth distribution, and financial inclusion, advocating for a balanced approach that maximizes benefits while minimizing negative outcomes. Preface 1 The Role of Autonomous Finance in the Era of Automatic Civilization 2 Analyzing the Latest Tools and Techniques for Stock Market Analysis 3 Challenges and Security Issues in Autonomous Finance 4 Involvement of Artificial Intelligence in Emerging Fintech Industry 4.0: A TCCM Framework 5 Robotic Process Automation in the Financial Sector 6 Integration of Fintech with Data Science (DS) and Artificial Intelligence (AI): A Challenging Footstep 7 Evaluation of Fintech: The Techno-Functional Application in Digital Banking 8 Real-Time Data Visualization and Autonomous Finance: Uses of Emerging Technologies 9 AI and ML Modeling and Autonomous Finance in Microfinance: An Overview 10 Application of Machine Learning Models in the Field of Autonomous Finance 11 Machine Learning Algorithm in Indian Stock Market for Revising and Refining the Equity Valuation Models 12 Hyper Automation and its Applicability in Automation Finance 13 Pre- and Post-COVID Autonomous Finance: Global Perspective