Deepa Gupta, PhD, is the Dean at GL Bajaj Institute of Management, Greater Noida, India. Her expertise extends to organized development, corporate relations, and international collaborations. Dr. Gupta is an active researcher who has published 15 national/international patents and has contributed more than 45 research papers to various international and national conferences and journals. Mukul Gupta, PhD, is a principal at GL Bajaj Institute of Management, Greater Noida, India. His research focuses on consumer behavior to help understand the human-centric aspects of autonomous finance systems. He has published 12 national/international patents, more than 40 research papers, and authored books. Rajesh Kumar Dhanaraj, PhD, is a professor at the School of Computing Science and Engineering at Galgotias University in India. He has authored/edited more than 25 books on various technologies, 21 patents, and 50+ articles and papers in various refereed journals and international conferences. Balamurugan Balusamy, PhD, is an associate dean of students at Shiv Nadar University at the Delhi-NCR Campus in Noida, India. He has authored/edited more than 80 books and more than 200 contributions to international journals and conferences. Parth Mukul Gupta, is an innovative entrepreneur and the director at Zarthcorp Tech Pvt. Ltd. and of the Shri Sai Memorial Foundation, Greater Noida, India. He has experience in brand building, organizational development, and global collaborations and spearheads advancements in autonomous finance through technological innovation and strategic growth initiatives.

• Preface xvii1 The Role of Autonomous Finance in the Era of Automatic Civilization 1Sanjeet Singh, Geetika Madaan and Jaskiran Kaur1.1 Introduction 21.2 The Concept of Autonomous Finance 21.3 Autonomous Finance: Prospects and Developments 91.4 Key Considerations for Implementing Autonomous Finance 141.5 Conclusion 152 Analyzing the Latest Tools and Techniques for Stock Market Analysis 21Ochin Sharma, Raj Gaurang Tiwari, Suvarna Sharma and Annu Priya2.1 Introduction 212.2 Need for Trading Softwares 232.3 How Software for Technical Analysis of the Indian Stock Market Operates 232.4 Helpful Tools to Analyze Stock Market 242.5 Conclusion 393 Challenges and Security Issues in Autonomous Finance 43Mukul Gupta, Deepa Gupta, Nitin Agrawal and Parth Mukul Gupta3.1 Introduction 443.2 A Review of the Literature 453.3 Concerns Regarding the Protection of Identity and Privacy in Autonomous Finance 463.4 Using Algorithms to Make Decisions Can be Biased 493.5 Ensuring Fairness in Autonomous Finance 503.6 Compliance with Regulations in the Field of Autonomous Finance 513.7 Gaining an Understanding of the Fundamentals of Operational Risk 543.8 Risks Encountered in the Operation of Autonomous Finance 553.9 Concerns Regarding Ethical Issues in Autonomous Finance 573.10 Consumer Trust in Autonomous Finance 594 Involvement of Artificial Intelligence in Emerging Fintech Industry 4.0: A TCCM Framework 65Annu and Ravindra Tripathi4.1 Introduction 664.2 Data and Methodology 694.3 Results and Discussion 704.4 Finding, Conclusion, and Research Directions 764.5 Summary 775 Robotic Process Automation in the Financial Sector 81Neha Sonik, Deepa Gupta and Parul Gupta5.1 Introduction 815.2 How are Financial Institutions Making Use of Robotics and Automation? 835.3 Major Use Cases of Robotic Process Automation in Banking and Finance 845.4 Minding Gaps in Financial Process Automation 915.5 The Key Benefits of Finance Automation 925.6 A List of Accounting and Financial Services Companies That are Using RPA 955.7 Steps to Deploy RPA in Banking and Finance 975.8 Conclusion 996 Integration of Fintech with Data Science (DS) and Artificial Intelligence (AI): A Challenging Footstep 101Ankur Goel, Monisha Awasthi, Anamika Rana and Sushma Malik6.1 Introduction 1026.2 Historical Background of Fintech 1026.3 Advantages of Fintech 1046.4 Role of Data Science and AI 1086.5 Data Science and AI (DSAI) Making Smart Fintech 1116.6 Use Cases of Data Science in Fintech 1166.7 Conclusion 1197 Evaluation of Fintech: The Techno-Functional Application in Digital Banking 123Priyanka Verma, Rajesh Kumar Dhanaraj, Deepa Gupta and Mukul Gupta7.1 Introduction 1237.2 Overview of Fintech 1247.3 Theoretical Overview 1367.4 Measurement of the Success Factor of Fintech in Digital Banking 1377.5 Summary 1398 Real-Time Data Visualization and Autonomous Finance: Uses of Emerging Technologies 143Govind Singh, Lokesh Verma and Anshika Baliyan8.1 Introduction 1448.2 Thriving in the Tech Age: How Businesses Adapt to Emerging Technologies 1488.3 The Future of Work and Innovation: Emerging Technologies Transforming Businesses 1518.4 Major Emerging Technologies in Finance 1598.5 Risk Associated with Emerging Technologies 1648.6 Conclusion 1659 AI and ML Modeling and Autonomous Finance in Microfinance: An Overview 167D. N. Rao and Maheswaran Mahalingam9.1 Understanding Autonomous Finance and Microfinance 1689.2 Readiness of MFIs for Autonomous Finance Transformation 1709.3 Solution Drivers in the Life Cycle Journey of an MFI Customer 1739.4 Readiness of MFIs for Autonomous Finance Operations 1779.5 Technology and AI and ML Enablers of Autonomous Finance for MFIs 1809.6 Critical Business Needs of Autonomous Finance 1829.7 AI and ML Analytical Models for MFIs 1829.8 Overall Deployment and Suitability 1889.9 Roadmap for Autonomous Finance in MFIs 1889.10 Stage-1: Operation Moonwalk 1909.11 Stage 2—Operation Sun Shine 1929.12 Stage 3 Operation Bloomsdale 1939.13 Improvement Opportunities of Autonomous Finance for MFIs 1939.14 Embracing Future AI Agents and Robotics of Autonomous Finance 19510 Application of Machine Learning Models in the Field of Autonomous Finance 199Umesh Gupta, Shriyash Saxena, Sachin Kumar Yadav and Aditya Bhardwaj10.1 Overview 19910.2 Introduction 20110.3 Reinforcement Learning 20310.4 Neural Network Basics 20910.5 Management of Information for Credit Risk 21310.6 Sentiment Analysis with Data Mining Approach 21510.7 Conclusion 21611 Machine Learning Algorithm in Indian Stock Market for Revising and Refining the Equity Valuation Models 221Nitha K. P., Suraj E. S. and Ranjith Karat11.1 Introduction 22111.2 Objectives of the Study 22311.3 Methodology 22311.4 Review of Literature 22511.5 Machine Learning for Equity Valuation Models 22811.6 Architecture of Refined Equity Models 23211.7 Analysis—Checking the Valuation Accuracy of Revised and Refined Models Using Machine Learning Approach 23411.8 Conclusion 24012 Hyper Automation and its Applicability in Automation Finance 243Pushpendra Pal Singh, Rakesh Kumar Dixit and Rajesh Kumar Dhanaraj12.1 Introduction 24412.2 Background 24512.3 Hyper Automation: Evolution, Technologies, and Impact in the Digital Era 24712.4 Automation-(2)-Hyper Automation: Gartner 24912.5 Could Hyper Automation be a Name for AI Plus RPA? 25012.6 Sophistication of the Automation 25212.7 Hyper Automation Process Flow 25412.8 Banking and Finance Applications 26012.9 Conclusions 26413 Pre- and Post-COVID Autonomous Finance: Global Perspective 269Shikha Singh, Deepa Gupta, Roshan Kumar and Balamurugan Balusamy13.1 Introduction 27013.2 Literature Review 27113.3 Factors Behind the Digitalization of Financial Services During the COVID Pandemic 27313.4 Challenges/Barriers for FinTech 27913.5 Advantages and Disadvantages of Market Structure Modifications Towards the Digitalization of FinTech Services 28013.6 Conclusion 28314 Emerging Trends and Future Directions in Artificial Intelligence for Next-Generation Computing 289Rafael Vargas-Bernal14.1 Introduction 29014.2 Concepts of Neuromorphic Computing, Artificial Intelligence, and Memristor 29114.3 Advantages of Two-Dimensional Materials Used in Neuromorphic Computing 29414.4 Devices Implemented with Two-Dimensional Materials to Evolve Artificial Intelligence 29814.5 Future Research Directions 30814.6 Summary 309Acknowledgments 310References 310Index 313

Deepa Gupta, PhD, is the Dean at GL Bajaj Institute of Management, Greater Noida, India. Her expertise extends to organized development, corporate relations, and international collaborations. Dr. Gupta is an active researcher who has published 15 national/international patents and has contributed more than 45 research papers to various international and national conferences and journals. Mukul Gupta, PhD, is a principal at GL Bajaj Institute of Management, Greater Noida, India. His research focuses on consumer behavior to help understand the human-centric aspects of autonomous finance systems. He has published 12 national/international patents, more than 40 research papers, and authored books. Rajesh Kumar Dhanaraj, PhD, is a professor at the School of Computing Science and Engineering at Galgotias University in India. He has authored/edited more than 25 books on various technologies, 21 patents, and 50+ articles and papers in various refereed journals and international conferences. Balamurugan Balusamy, PhD, is an associate dean of students at Shiv Nadar University at the Delhi-NCR Campus in Noida, India. He has authored/edited more than 80 books and more than 200 contributions to international journals and conferences. Parth Mukul Gupta, is an innovative entrepreneur and the director at Zarthcorp Tech Pvt. Ltd. and of the Shri Sai Memorial Foundation, Greater Noida, India. He has experience in brand building, organizational development, and global collaborations and spearheads advancements in autonomous finance through technological innovation and strategic growth initiatives.

• Preface xvii1 The Role of Autonomous Finance in the Era of Automatic Civilization 1Sanjeet Singh, Geetika Madaan and Jaskiran Kaur1.1 Introduction 21.2 The Concept of Autonomous Finance 21.3 Autonomous Finance: Prospects and Developments 91.4 Key Considerations for Implementing Autonomous Finance 141.5 Conclusion 152 Analyzing the Latest Tools and Techniques for Stock Market Analysis 21Ochin Sharma, Raj Gaurang Tiwari, Suvarna Sharma and Annu Priya2.1 Introduction 212.2 Need for Trading Softwares 232.3 How Software for Technical Analysis of the Indian Stock Market Operates 232.4 Helpful Tools to Analyze Stock Market 242.5 Conclusion 393 Challenges and Security Issues in Autonomous Finance 43Mukul Gupta, Deepa Gupta, Nitin Agrawal and Parth Mukul Gupta3.1 Introduction 443.2 A Review of the Literature 453.3 Concerns Regarding the Protection of Identity and Privacy in Autonomous Finance 463.4 Using Algorithms to Make Decisions Can be Biased 493.5 Ensuring Fairness in Autonomous Finance 503.6 Compliance with Regulations in the Field of Autonomous Finance 513.7 Gaining an Understanding of the Fundamentals of Operational Risk 543.8 Risks Encountered in the Operation of Autonomous Finance 553.9 Concerns Regarding Ethical Issues in Autonomous Finance 573.10 Consumer Trust in Autonomous Finance 594 Involvement of Artificial Intelligence in Emerging Fintech Industry 4.0: A TCCM Framework 65Annu and Ravindra Tripathi4.1 Introduction 664.2 Data and Methodology 694.3 Results and Discussion 704.4 Finding, Conclusion, and Research Directions 764.5 Summary 775 Robotic Process Automation in the Financial Sector 81Neha Sonik, Deepa Gupta and Parul Gupta5.1 Introduction 815.2 How are Financial Institutions Making Use of Robotics and Automation? 835.3 Major Use Cases of Robotic Process Automation in Banking and Finance 845.4 Minding Gaps in Financial Process Automation 915.5 The Key Benefits of Finance Automation 925.6 A List of Accounting and Financial Services Companies That are Using RPA 955.7 Steps to Deploy RPA in Banking and Finance 975.8 Conclusion 996 Integration of Fintech with Data Science (DS) and Artificial Intelligence (AI): A Challenging Footstep 101Ankur Goel, Monisha Awasthi, Anamika Rana and Sushma Malik6.1 Introduction 1026.2 Historical Background of Fintech 1026.3 Advantages of Fintech 1046.4 Role of Data Science and AI 1086.5 Data Science and AI (DSAI) Making Smart Fintech 1116.6 Use Cases of Data Science in Fintech 1166.7 Conclusion 1197 Evaluation of Fintech: The Techno-Functional Application in Digital Banking 123Priyanka Verma, Rajesh Kumar Dhanaraj, Deepa Gupta and Mukul Gupta7.1 Introduction 1237.2 Overview of Fintech 1247.3 Theoretical Overview 1367.4 Measurement of the Success Factor of Fintech in Digital Banking 1377.5 Summary 1398 Real-Time Data Visualization and Autonomous Finance: Uses of Emerging Technologies 143Govind Singh, Lokesh Verma and Anshika Baliyan8.1 Introduction 1448.2 Thriving in the Tech Age: How Businesses Adapt to Emerging Technologies 1488.3 The Future of Work and Innovation: Emerging Technologies Transforming Businesses 1518.4 Major Emerging Technologies in Finance 1598.5 Risk Associated with Emerging Technologies 1648.6 Conclusion 1659 AI and ML Modeling and Autonomous Finance in Microfinance: An Overview 167D. N. Rao and Maheswaran Mahalingam9.1 Understanding Autonomous Finance and Microfinance 1689.2 Readiness of MFIs for Autonomous Finance Transformation 1709.3 Solution Drivers in the Life Cycle Journey of an MFI Customer 1739.4 Readiness of MFIs for Autonomous Finance Operations 1779.5 Technology and AI and ML Enablers of Autonomous Finance for MFIs 1809.6 Critical Business Needs of Autonomous Finance 1829.7 AI and ML Analytical Models for MFIs 1829.8 Overall Deployment and Suitability 1889.9 Roadmap for Autonomous Finance in MFIs 1889.10 Stage-1: Operation Moonwalk 1909.11 Stage 2—Operation Sun Shine 1929.12 Stage 3 Operation Bloomsdale 1939.13 Improvement Opportunities of Autonomous Finance for MFIs 1939.14 Embracing Future AI Agents and Robotics of Autonomous Finance 19510 Application of Machine Learning Models in the Field of Autonomous Finance 199Umesh Gupta, Shriyash Saxena, Sachin Kumar Yadav and Aditya Bhardwaj10.1 Overview 19910.2 Introduction 20110.3 Reinforcement Learning 20310.4 Neural Network Basics 20910.5 Management of Information for Credit Risk 21310.6 Sentiment Analysis with Data Mining Approach 21510.7 Conclusion 21611 Machine Learning Algorithm in Indian Stock Market for Revising and Refining the Equity Valuation Models 221Nitha K. P., Suraj E. S. and Ranjith Karat11.1 Introduction 22111.2 Objectives of the Study 22311.3 Methodology 22311.4 Review of Literature 22511.5 Machine Learning for Equity Valuation Models 22811.6 Architecture of Refined Equity Models 23211.7 Analysis—Checking the Valuation Accuracy of Revised and Refined Models Using Machine Learning Approach 23411.8 Conclusion 24012 Hyper Automation and its Applicability in Automation Finance 243Pushpendra Pal Singh, Rakesh Kumar Dixit and Rajesh Kumar Dhanaraj12.1 Introduction 24412.2 Background 24512.3 Hyper Automation: Evolution, Technologies, and Impact in the Digital Era 24712.4 Automation-(2)-Hyper Automation: Gartner 24912.5 Could Hyper Automation be a Name for AI Plus RPA? 25012.6 Sophistication of the Automation 25212.7 Hyper Automation Process Flow 25412.8 Banking and Finance Applications 26012.9 Conclusions 26413 Pre- and Post-COVID Autonomous Finance: Global Perspective 269Shikha Singh, Deepa Gupta, Roshan Kumar and Balamurugan Balusamy13.1 Introduction 27013.2 Literature Review 27113.3 Factors Behind the Digitalization of Financial Services During the COVID Pandemic 27313.4 Challenges/Barriers for FinTech 27913.5 Advantages and Disadvantages of Market Structure Modifications Towards the Digitalization of FinTech Services 28013.6 Conclusion 28314 Emerging Trends and Future Directions in Artificial Intelligence for Next-Generation Computing 289Rafael Vargas-Bernal14.1 Introduction 29014.2 Concepts of Neuromorphic Computing, Artificial Intelligence, and Memristor 29114.3 Advantages of Two-Dimensional Materials Used in Neuromorphic Computing 29414.4 Devices Implemented with Two-Dimensional Materials to Evolve Artificial Intelligence 29814.5 Future Research Directions 30814.6 Summary 309Acknowledgments 310References 310Index 313