The Impact of Artificial Intelligence on Governance, Economics and Finance, Volume 2 (Accounting, Finance, Sustainability, Governance & Fraud: Theory and Application)

This book continues the discussion of the effects of artificial intelligence in terms of economics and finance. In particular, the book focuses on the effects of the change in the structure of financial markets, institutions and central banks, along with digitalization analyzed based on fintech ecosystems. In addition to finance sectors, other sectors, such as health, logistics, and industry 4.0, all of which are undergoing an artificial intelligence induced rapid transformation, are addressed in this book. Readers will receive an understanding of an integrated approach towards the use of artificial intelligence across various industries and disciplines with a vision to address the strategic issues and priorities in the dynamic business environment in order to facilitate decision-making processes. Economists, board members of central banks, bankers, financial analysts, regulatory authorities, accounting and finance professionals, chief executive officers, chiefaudit officers and chief financial officers, chief financial officers, as well as business and management academic researchers, will benefit from reading this book. Foreword Contents Editor and Contributors List of Figures List of Tables Part I Introduction 1 Introduction 1.1 Introduction References Part II The Impact of AI on Smart Systems 2 An Integrated Model and Application for Smart Building Systems with Artificial Intelligence 2.1 Introduction 2.2 Literature Review 2.3 Brief Information About Some Software, Hardware, and Techniques 2.3.1 Smart Screens 2.3.2 Raspberry Pi 2.3.3 IBeacon 2.3.4 Web Programming Tools 2.3.5 Matlab 2.3.6 Python 2.3.7 Java 2.3.8 Unity 2.3.9 Vuforia 2.4 Analytical Hierarchical Process (AHP) 2.4.1 Computer Vision (CV) 2.4.2 Text to Speech 2.4.3 Augmented Reality 2.5 Information About the Developed Model 2.5.1 System Design 2.5.2 Intelligent Evacuation System (IES) 2.5.3 Smart Guest Guidance System (SGGS) 2.5.4 Smart Media System (SMS) 2.5.5 Intelligent Staff Monitoring System (ISMS) 2.5.6 Smart Survey System (SSS) 2.5.7 Intelligent Building Information System (IBIS) 2.6 Conclusion and Recommendations References 3 Artificial Intelligence for Smart Cities: Locational Planning and Dynamic Routing of Emergency Vehicles 3.1 Introduction 3.2 Routing Problems 3.2.1 The CVRP Model 3.2.2 Vehicle Routing Problem Extensions 3.3 Ambulance Location/Relocation Problems 3.4 Applications in Healthcare Logistics for Smart Cities 3.5 Conclusion References 4 The “Transformative” Effect of Artificial Intelligence Systems (AIS) in Entrepreneurship 4.1 Introduction 4.2 How Will AIS Affect the Entrepreneurship Classification and the Way Entrepreneurs Do Business? 4.3 How Will AIS Transform the Big Picture Through Entrepreneurship? 4.4 What Can Be the Usage Areas of AIS for Entrepreneurs? 4.5 How Will AISs Affect Entrepreneurship Education? 4.6 How Will AIS Affect Entrepreneurship Research? 4.7 What Will AIS and Entrepreneurship-Based Research Questions Be? Curious Topics... 4.8 Should We Call It the End or the Beginning...? References 5 A Machine Learning Framework for Data-Driven CRM 5.1 Introduction 5.2 Literature Review 5.2.1 CRM 5.2.2 Machine Learning Techniques 5.3 Proposed Framework 5.3.1 Problem Formulation and Machine Learning Technique Selection 5.3.2 Data Preparation and Pre-Processing 5.3.3 Application of Machine Learning Algorithms 5.3.4 Evaluation 5.3.5 Analysis of Results 5.4 Conclusion References Part III The Impact of AI on Accounting, Finance and Fraud 6 How Blockchain and Artificial Intelligence Will Effect the Cloud-Based Accounting Information Systems? 6.1 Introduction 6.1.1 Cloud-Based Accounting 6.1.2 Artificial Intelligence 6.1.3 Triple-Entry Accounting Based on Blockchain 6.2 The Synergy of AI and Blockchain 6.3 Conclusion References 7 Machine Learning Applications for Fraud Detection in Finance Sector 7.1 Introduction 7.2 Financial Fraud 7.2.1 Bank Fraud 7.2.2 Insurance Fraud 7.2.3 Corporate Fraud 7.3 Machine Learning Applications for Financial Fraud Detection 7.3.1 Machine Learning 7.3.2 Unsupervised Learning 7.4 Ensemble Learning 7.4.1 Bagging 7.4.2 Boosting 7.4.3 Stacking 7.4.4 Voting 7.5 Deep Learning 7.5.1 Convolutional Neural Network (CNN) 7.5.2 Autoencoder 7.6 Statistics of Machine Learning-Based Fraud Detection Studies 7.7 Conclusion References 8 The Importance of Graph Databases in Detection of Organized Financial Crimes 8.1 Introduction 8.2 Literature Review 8.2.1 Comparison of Relational and Graph Databases in Terms of Revealing the Relationships Between Different Entities 8.2.2 Case Study 8.3 Conclusion References 9 Practices of Natural Language Processing in the Finance Sector 9.1 Introduction 9.2 Financial Forecasting Using NLP Methods 9.2.1 Lexical Analysis 9.2.2 Syntactic Analysis 9.2.3 Text Representation Approaches: Bag of Words (BoW) 9.2.4 Semantic Analysis 9.3 Detecting Sensitive Information Using NLP Methods 9.3.1 Named Entity Recognition (NER) 9.3.2 Domain Ontologies for Sensitive Data Detection 9.4 Conclusion References Part IV Specialized Topics on AI Implementations 10 Higher Education and Labor Market Transformation in the Era of Industry 4.0 in a Developing Country: The Case for Turkey 10.1 Introduction 10.2 Data 10.2.1 Synthetic Control Method 10.3 Results 10.3.1 Manufacture of Textiles 10.3.2 Manufacture of Food Products 10.3.3 Manufacture of Motor Vehicles, Trailers, and Semi-Trailers 10.3.4 Manufacture of Other Transport Equipment 10.3.5 Manufacture of Furniture Sectors 10.3.6 Overview of the Results and Education Policy 10.4 Conclusion Appendix References 11 The Role of Artificial Intelligence in Health Care 11.1 Introduction 11.2 Key Technologies for AI in Health Care 11.2.1 Natural Language Processing (NLP) 11.2.2 Machine Learning (ML) 11.2.3 Virtual Agents 11.2.4 Decision Management/Clinical Decision Support Systems (CDSS) 11.2.5 Intelligent Decision Support Systems (IDSS) 11.2.6 Deep Learning 11.2.7 Computer Vision and Image Recognition 11.3 Applications of AI in Health Care 11.3.1 Identifying Diseases and Diagnosis 11.3.2 Drug Discovery and Manufacturing 11.3.3 Medical Imaging Diagnosis 11.3.4 Precision Medicine 11.3.5 Robotic Surgery 11.3.6 Electronic Health Records—EHR 11.3.7 Doing Repetitive Jobs 11.3.8 Telehealth, Telemedicine, and Digital Consultation 11.3.9 Virtual Nurses and Virtual Medical Assistants 11.3.10 Health Monitoring 11.3.11 Healthcare System Analysis and Management 11.3.12 Outbreak Prediction 11.4 Drawbacks and Ethical Issues 11.5 Conclusions References 12 An Overview of New Generation Bio-Inspired Algorithms for Portfolio Optimization 12.1 Introduction 12.2 Portfolio Optimization Models 12.2.1 Real-Life Portfolio Constraints 12.3 Classical Bio-Inspired Algorithms in Portfolio Optimization 12.4 New Generation Bio-Inspired Algorithms in Portfolio Optimization 12.4.1 Artificial Bee Colony Optimization 12.4.2 Bacterial Foraging Optimization 12.4.3 Bat Algorithm 12.4.4 Biogeography-based Optimization 12.4.5 Cuckoo Search 12.4.6 Firefly Algorithm 12.4.7 Harmony Search 12.5 Other Recent Bio-Inspired Algorithms in Portfolio Optimization 12.6 Conclusion References 13 The Effects of Artificial Intelligence on the Insurance Sector: Emergence, Applications, Challenges, and Opportunities 13.1 Introduction 13.2 Related Studies 13.3 A Brief History and the Concept of Artificial Intelligence 13.4 Emergence of Artificial Intelligence in the Insurance Sector 13.4.1 Artificial Intelligence in Global Insurance Sector 13.4.2 Artificial Intelligence in Turkish Insurance Sector 13.5 The Effects of Artificial Intelligence on the Insurance Sector 13.5.1 Challenges and Barriers 13.5.2 Opportunities 13.5.3 Future Trends 13.6 Conclusion References 14 Understanding the Utilization of Artificial Intelligence and Robotics in the Service Sector 14.1 Introduction 14.2 Service Robots 14.3 Impact of Robots on Service Provision 14.3.1 Impacts on Customers 14.3.2 Impacts on Employees 14.4 Theories and Frameworks on the Acceptance and Use of Service Robots 14.5 Empirical and Experimental Studies Related to Use of Service Robots 14.6 Conceptual Studies Related to Use of Service Robots 14.7 Conclusion References Index Economists, board members of central banks, bankers, financial analysts, regulatory authorities, accounting and finance professionals, chief executive officers, chief audit officers and chief financial officers, chief financial officers, as well as business and management academic researchers, will benefit from reading this book.