Data-Driven Modelling and Predictive Analytics in Business and Finance
Auerbach (Verlag)
978-1-032-60062-8 (ISBN)
Data-driven and AI-aided applications are next-generation technologies that can be used to visualize and realize intelligent transactions in finance, banking, and business. These transactions will be enabled by powerful data-driven solutions, IoT technologies, AI-aided techniques, data analytics, and visualization tools. To implement these solutions, frameworks will be needed to support human control of intelligent computing and modern business systems. The power and consistency of data-driven competencies are a critical challenge, and so is developing explainable AI (XAI) to make data-driven transactions transparent.
Data- Driven Modelling and Predictive Analytics in Business and Finance covers the need for intelligent business solutions and applications. Explaining how business applications use algorithms and models to bring out the desired results, the book covers:
Data-driven modelling
Predictive analytics
Data analytics and visualization tools
AI-aided applications
Cybersecurity techniques
Cloud computing
IoT-enabled systems for developing smart financial systems
This book was written for business analysts, financial analysts, scholars, researchers, academics, professionals, and students so they may be able to share and contribute new ideas, methodologies, technologies, approaches, models, frameworks, theories, and practices.
Alex Khang is a Professor of Information Technology, D.Sc. D.Litt., and a AI and Data scientist, AI and Data Science Research Center, Global Research Institute of Technology and Engineering, North Carolina, United States. Rashmi Gujrati is a Professor, Campus Director, and Dean of International Affairs at Kamal Gandhi Memorial Ayurvedic College, Nawanshahr, India. Hayri Uygun holds a Ph.D. from Recep Tayyip Erdogan University, Institute of Social Sciences, Business Administration, Rize, Turkey. R. K. Tailor is an expert in robotic process automation and robotic accounting and a Senior Associate Professor at the Department of Business Administration, Manipal University, Manipal, India. Sanjaya Singh Gaur is a Clinical Professor of Marketing at the NYU School of Professional Studies in New York University, New York, United States.
1. Application of Data Technologies and Tools in Business and Finance Sectors 2. Data Analytics Tools and Applications for Business and Finance Systems 3. Big Data Tools for Business and Finance Sectors in the Era of Metaverse 4. Digital Revolution and Innovation in the Banking and Finance Sectors 5. Impact of AI and Data in Revolutionizing Microfinance in Development Countries: Improving Outreach and Efficiency 6. Digital Payments: The Growth Engine of the Digital Economy 7. Machine Learning-Based Functionalities for Business Intelligence and Data Analytics Tools 8. A Study of Domain-Specific Approach in Business Using Big Data Analytics and Visualization 9. Cloud-Based Data Management for Behavior Analytics in Business and Finance Sectors 10. Theoretical Analysis and Data Modeling of the Influence of Shadow Banking on Systemic Risk 11. The Potential of Fintech-Driven Model in Enabling Financial Inclusion 12. Predicting Impact of Exchange Rate Volatility on Sectoral Indices 13. Digital Competency Assessment and Data-Driven Performance Management for Start-Ups 14. Blockchain Technologies and Applications for Business and Finance Systems 15. Analyzing the Reaction for M&A of Rivals in Emerging Market Economy 16. Management Model 6.0 and SWOT Analysis for the Market Share of Product in the Global Market 17. Human-Centred and Design Thinking Approaches for Predictive Analytics 18. Co-Integration and Causality between Macroeconomics Variables and Bitcoin 19. An Examination of Data Protection and Cyber Frauds in the Financial Sector 20. The ChatGPT’s Influence on the Job Market - An Analytical Study 21. Cloud Data Security Using Advanced Encryption Standard with Ant Colony Optimization in Business Sector 22. Cybersecurity Techniques for Business and Finance Systems
| Erscheinungsdatum | 10.07.2024 |
|---|---|
| Reihe/Serie | Advances in Computational Collective Intelligence |
| Zusatzinfo | 67 Tables, black and white; 75 Line drawings, color; 23 Line drawings, black and white; 98 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 816 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| Wirtschaft ► Betriebswirtschaft / Management | |
| Wirtschaft ► Volkswirtschaftslehre | |
| ISBN-10 | 1-032-60062-4 / 1032600624 |
| ISBN-13 | 978-1-032-60062-8 / 9781032600628 |
| Zustand | Neuware |
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