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The AI book : the artificial intelligence handbook for investors, entrepreneurs and fintech visionaries / / edited by Susanne Chishti [and three others]
| The AI book : the artificial intelligence handbook for investors, entrepreneurs and fintech visionaries / / edited by Susanne Chishti [and three others] |
| Autore | Chishti Susanne |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | United Kingdom : , : Wiley, , 2020 |
| Descrizione fisica | 1 online resource (421 pages) : illustrations |
| Disciplina | 332.0285/63 |
| Soggetto topico |
Financial services industry - Information technology
Finance - Technological innovations Artificial intelligence - Financial applications |
| ISBN |
1-119-55186-2
1-119-55192-7 1-119-55196-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910555049503321 |
Chishti Susanne
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| United Kingdom : , : Wiley, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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AI in the Financial Markets : New Algorithms and Solutions / / Federico Cecconi, editor
| AI in the Financial Markets : New Algorithms and Solutions / / Federico Cecconi, editor |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (140 pages) |
| Disciplina | 332.028563 |
| Collana | Computational Social Sciences Series |
| Soggetto topico | Artificial intelligence - Financial applications |
| ISBN |
9783031265181
9783031265174 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Artificial Intelligence and Financial Markets -- Chapter 2. AI, the overall picture -- Chapter 3. Financial markets: values, dynamics, problems -- Chapter 4. The AI's Role in the Great Reset -- Chapter 5. AI Fintech: find out the truth -- Chapter 6. ABM applications to Financial Markets -- Chapter 7. ML application to the Financial Market -- Chapter 8. AI tools for pricing of distressed asset utp and npl loan portfolios -- Chapter 9. More than data science: FuturICT 2.0 -- Chapter 10. Opinion dynamics. |
| Record Nr. | UNINA-9910683341803321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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AI in the Financial Markets : New Algorithms and Solutions / / Federico Cecconi, editor
| AI in the Financial Markets : New Algorithms and Solutions / / Federico Cecconi, editor |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (140 pages) |
| Disciplina | 332.028563 |
| Collana | Computational Social Sciences Series |
| Soggetto topico | Artificial intelligence - Financial applications |
| ISBN |
9783031265181
9783031265174 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Artificial Intelligence and Financial Markets -- Chapter 2. AI, the overall picture -- Chapter 3. Financial markets: values, dynamics, problems -- Chapter 4. The AI's Role in the Great Reset -- Chapter 5. AI Fintech: find out the truth -- Chapter 6. ABM applications to Financial Markets -- Chapter 7. ML application to the Financial Market -- Chapter 8. AI tools for pricing of distressed asset utp and npl loan portfolios -- Chapter 9. More than data science: FuturICT 2.0 -- Chapter 10. Opinion dynamics. |
| Record Nr. | UNISA-996546826703316 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Application of AI in credit scoring modeling / / Bohdan Popovych
| Application of AI in credit scoring modeling / / Bohdan Popovych |
| Autore | Popovych Bohdan |
| Pubbl/distr/stampa | Wiesbaden, Germany : , : Springer Gabler, , [2022] |
| Descrizione fisica | 1 online resource (93 pages) |
| Disciplina | 332.640285 |
| Collana | BestMasters |
| Soggetto topico |
Artificial intelligence - Financial applications
Credit scoring systems |
| ISBN |
9783658401801
9783658401795 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intro -- Foreword -- Abstract -- Contents -- Abbreviations -- List of Figures -- List of Tables -- 1 Introduction -- 2 Theoretical Concepts of Credit Scoring -- 2.1 Literature Background -- 2.2 Theoretical Overview -- 2.2.1 Definition and Application -- 2.2.2 Advantages and Limitations -- 2.2.3 Comparison of Credit Scoring and Credit Rating -- 2.3 Regulatory Requirements -- 3 Credit Scoring Methodologies -- 3.1 Traditional Credit Scoring Techniques -- 3.1.1 Discriminant Analysis -- 3.1.2 Logistic Regression -- 3.1.3 Expert Systems -- 3.2 Artificial Intelligence Classification Methods -- 3.2.1 Overview of AI Classification Techniques -- 3.2.2 Decision Trees -- 3.2.3 Random Forest -- 3.3 Methods of Model Validation -- 4 Empirical Analysis -- 4.1 Data Analysis -- 4.2 Logistic Regression -- 4.2.1 Model Description -- 4.2.2 Model Interpretation -- 4.2.3 Model Performance -- 4.3 Decision Tree -- 4.3.1 Model Description and Interpretation -- 4.3.2 Model Performance -- 4.4 Random Forest -- 4.4.1 Model Description -- 4.4.2 Model Interpretation -- 4.4.3 Model Performance -- 4.5 Models Comparison -- 5 Conclusion -- References. |
| Record Nr. | UNINA-9910634052603321 |
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Popovych Bohdan
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| Wiesbaden, Germany : , : Springer Gabler, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial financial intelligence in China / / Dawei Zhao, Wenting Zhang
| Artificial financial intelligence in China / / Dawei Zhao, Wenting Zhang |
| Autore | Zhao Dawei |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (200 pages) |
| Disciplina | 332.028563 |
| Collana | Financial mathematics and FinTech |
| Soggetto topico | Artificial intelligence - Financial applications |
| ISBN | 981-16-5592-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgments -- Contents -- Chapter 1: FinTech Towards Intelligent Finance -- 1.1 The Rise of AI Finance -- 1.1.1 Global Trends in Artificial Intelligence Development -- 1.1.2 What is Intelligent Finance? -- 1.1.3 Features of Intelligent Finance -- 1.1.3.1 Self-Learning Intelligent Technology -- 1.1.3.2 Ecological Cooperation with Closed-Loop Data -- 1.1.3.3 Technology Driven Business Innovation -- 1.2 Application of Artificial Intelligence in the Financial Field -- 1.2.1 Improved Efficiency of Financial Transactions -- 1.2.2 Provision of Intelligent Financial Management Service -- 1.2.3 Development of a Disruptive Business Model for the Insurance Industry -- 1.2.4 Improved Customer Service Experience -- 1.2.5 Robotic Process Automation -- 1.2.6 Information Extraction and Compliance and Fraud Prevention Using Image Recognition -- 1.2.7 Improved Credit Scoring and Credit Loan Services -- 1.3 The Development Stages of FinTech in China -- 1.3.1 Computerized Financial Services -- 1.3.2 Financial Informatization -- 1.3.3 Internet Finance -- 1.3.4 Intelligent Finance -- 1.4 The Impact of Artificial Intelligence on the Financial Industry -- 1.4.1 Crowding Out Risks Introduced by Disruptive Technologies -- 1.4.2 Challenges to Data Security and Personal Privacy Protection -- 1.4.3 The Abuse of Facial Recognition Technology -- 1.4.4 Technical Risks Caused by Algorithm Black Box and Algorithm Discrimination -- 1.4.5 The Humanized Development of Artificial Intelligence -- Chapter 2: Scientific and Technological Supervision of Artificial Intelligence -- 2.1 The International Status of Artificial Intelligence Supervision -- 2.1.1 The USA-Guide by Framework and Legislate Normatively -- 2.1.2 The European Union-Rules First, Focus on the Protection of Human Rights.
2.1.2.1 The EU´s Objective in Artificial Intelligence: Assess Which Technologies Pose a Threat to Fundamental Human Rights -- 2.1.2.2 Chief Concern of the European Commission: Ethical Standards -- 2.1.2.3 European Commission Supervision of Artificial Intelligence: A Process of Continuous Exploration -- 2.1.2.4 The EU´s Existing Laws and Regulations on the Supervision of FinTech -- 2.1.3 The United Kingdom-Supervision Within the Framework of Laws and Guidelines -- 2.1.4 Canada-Lead by Strategies and Guide by Principles -- 2.1.4.1 Guiding Principles for Artificial Intelligence -- 2.1.4.2 List of Artificial Intelligence Suppliers -- 2.1.4.3 Algorithmic Impact Assessment (AIA) -- 2.1.4.4 Directive on Automated Decision-Making -- 2.1.4.5 Strategic Plan for Information Management and Information Technology 2017-2021 -- 2.1.5 Japan-Promote Development with Supervision and Focus on Employees´ Ethics -- 2.1.5.1 Unique Aspects in the Application of Artificial Intelligence in Japan -- 2.1.5.2 Japan´s Artificial Intelligence Society 5.0 -- 2.1.6 Hong Kong-Early Stages of Supervision and the Clarification of Basic Principles -- 2.1.7 Singapore-Guided by Plans and Extensive Cooperation -- 2.2 Development Background and Function of ``Artificial Intelligence + Financial Supervision´´ -- 2.2.1 Background Analysis of ``Artificial Intelligence + Financial Supervision´´ -- 2.2.2 The Role of ``Artificial Intelligence + Financial Supervision´´ -- 2.2.2.1 Provide Technical Solutions for Financial Regulatory Agencies to Reduce Regulatory Pressure and Costs -- 2.2.2.2 Deal Effectively with the Risks of ``Technology + Finance´´ -- 2.2.2.3 Give Birth to a New Industry -- 2.3 New Risks and New Challenges -- 2.3.1 Increased Complexity and Scope of Risk -- 2.3.2 Illegal Operation -- 2.3.3 Challenges for Financial Consumer Protection. 2.3.4 Insufficient Attention to Warning and Preventive Measures -- 2.3.5 Technical Risks and Data Risks -- 2.3.6 Regulatory Arbitrage -- 2.4 China´s Intelligent Financial Supervision Development Status -- 2.4.1 China Banking and Insurance Regulatory Commission Practice -- 2.4.2 China Securities Regulatory Commission Practice -- 2.4.3 Beijing´s Practice-``Beijing Financial Risk Control Cockpit´´ -- 2.4.4 Guangzhou, Xi ´an and Tianjin´s Practice- ``Ant Risk Brain´´ -- 2.4.5 Shenzhen´s Practice-``Lingkun Financial Security Big Data Platform´´ -- 2.4.6 Ningbo´s Practice- ``Tianluo Diwang´´ Financial Risk Monitoring and Control System -- 2.4.6.1 Risk Monitoring -- 2.4.6.2 Risk Early Warning -- 2.4.6.3 Risk Disposal -- 2.4.6.4 Institutional Supervision -- 2.4.6.5 Statistical Assessment -- 2.4.7 Analysis of Existing Problems in the Development Process of ``Artificial Intelligence + Financial Supervision´´ in China -- 2.4.7.1 Insufficient Planning -- 2.4.7.2 Lag in Development of Rules and Standards -- 2.4.7.3 Insufficient Overall Technical Ability -- 2.4.7.4 Risks Inherent in the Technology -- 2.4.7.5 Unbalanced Development and Application of Different Systems -- 2.5 Policy Suggestions on Artificial Intelligence Research and Development and Application in Financial Supervision -- 2.5.1 Understanding the Scope and Ability of ``Artificial Intelligence + Financial Supervision´´ -- 2.5.2 Formulating a Basic Rule System and Strengthening Standardization -- 2.5.3 Building a Risk Early Warning System, and Strengthening the Ability of Financial Regulatory Institutions to Prevent and ... -- 2.5.4 Monitoring the Business Behaviours of FinTech Suppliers -- 2.5.5 Grasping the New Challenges of Financial Consumer Protection -- 2.5.6 Enhancing International Cooperation -- Chapter 3: Technical Path of Artificial Intelligence Compliance Efficiency. 3.1 Development Status of CompTech -- 3.1.1 The Development Scale of CompTech -- 3.1.2 Application Scenarios of CompTech -- 3.2 Application of CompTech -- 3.2.1 Data Processing and Analysis, Optimization of Compliance Construction -- 3.2.2 Identity Verification and Management, Financial Crime Prevention -- 3.2.3 Compliance Review and Evaluation, Reduction of Compliance Costs -- 3.2.4 Risk Early Warning and Testing, Improved Prediction Ability -- 3.3 Challenges and Risks of CompTech -- 3.3.1 Limitations of the Algorithm Decision -- 3.3.2 Lack of Support System -- 3.3.3 Quality and Security of Data and Information -- 3.3.4 The Legal Risk of Liability Confirmation -- 3.3.5 Policy Suggestions for Promoting the Development of Compliance Technology -- 3.3.5.1 Regulatory Big Data Platform -- 3.3.5.2 Technical Management to Protect Consumer Rights and Interests -- 3.3.5.3 Coordinated Development of Compliance and Supervision -- 3.3.5.4 Unified Standards and Improved Supporting Guarantee Mechanism -- Chapter 4: Smart Payment in China -- 4.1 Application Mode of Smart Payment -- 4.1.1 Front-end Application Mode -- 4.1.1.1 Smart Account -- 4.1.1.2 Tools for Smart Payment -- 4.1.1.3 Smart Customer Service -- 4.1.2 Back-end Application Mode -- 4.1.2.1 Precise Service Provision -- 4.1.2.2 Intelligent Regulation -- 4.2 Application Scenario of Smart Payment -- 4.2.1 Application Scenario of AI Payment Abroad -- 4.2.1.1 Application Scenario of AI Payment Abroad in the Financial Industry -- 4.2.1.2 Multi-dimensional Application Scenario of AI Payment Abroad -- 4.2.2 Application Scenario of AI Payment in China -- 4.2.2.1 Application Scenario of AI Payment in China´s Financial Industry -- 4.2.2.2 Multi-dimensional Application Scenario of AI Payment in China -- 4.3 Strengths and Deficiencies of Smart Payment -- 4.3.1 Strengths of AI Payment. 4.3.1.1 Improves Payment Security -- 4.3.1.2 Improves Payment Efficiency -- 4.3.1.3 Optimizes Supply and Demand Matching -- 4.3.2 Deficiencies of AI Payment -- 4.3.2.1 Defective Laws and Regulations -- 4.3.2.2 Immature Products or Services -- 4.3.2.3 Ambiguous Regulatory Position -- 4.3.2.4 Insufficient Depth and Breadth of Technology Application -- 4.3.2.5 Unbalanced Reserve of Talents -- 4.4 Smart Payment Risks -- 4.4.1 Information Security Risk -- 4.4.2 Legal Risk -- 4.4.3 Technical Risk -- 4.4.4 Regulatory Risk -- 4.4.5 Systemic Risk -- 4.5 Policy Suggestions for Developing AI in Payment -- 4.5.1 Complete the Legal System -- 4.5.2 Stipulate Data Standard -- 4.5.3 Clarify Rights and Responsibility of Regulation -- 4.5.4 Optimize the Upgrade of AI Technology -- 4.5.5 Strengthen Security Assessment -- 4.5.6 Cultivate Inter-disciplinary Talent -- 4.5.7 Implement Protection Mechanism -- Chapter 5: Opportunities, Risks, and Breakdowns Brought by AI to Commercial Banks -- 5.1 Commercial Banks and Scientific and Technological Development -- 5.1.1 The Relationship Between Commercial Banks and Information Technology -- 5.1.2 Weak Spots of Commercial Bank Business -- 5.1.3 Digital Transformation of Commercial Banks -- 5.2 Application of AI in Commercial Banks -- 5.2.1 Motivation for Commercial Banks to Apply AI -- 5.2.2 Current Situation of AI Application in Commercial Banks -- 5.2.2.1 Intelligent Marketing -- 5.2.2.2 Intelligent Credit -- 5.2.2.3 Intelligent Customer Service -- 5.2.2.4 Intelligent Investment Advisor -- 5.2.2.5 Intelligent Operation -- 5.2.2.6 Intelligent Risk Control -- 5.2.3 The Positive Effect of AI Application in Commercial Banks -- 5.2.4 Potential Risks of AI Application in Commercial Banks -- 5.2.4.1 Traditional Financial Risk -- 5.2.4.2 Information Technology Risk -- 5.2.4.3 Data Leakage Risk -- 5.2.4.4 Market Monopoly Risk. 5.2.4.5 Network Attack Risk. |
| Record Nr. | UNINA-9910506399203321 |
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Zhao Dawei
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| Gateway East, Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial intelligence for financial markets : the polymodel approach / / Thomas Barrau and Raphael Douady
| Artificial intelligence for financial markets : the polymodel approach / / Thomas Barrau and Raphael Douady |
| Autore | Barrau Thomas |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (182 pages) |
| Disciplina | 332.64028563 |
| Collana | Financial Mathematics and Fintech |
| Soggetto topico |
Artificial intelligence - Financial applications
Inversions Estadística matemàtica Intel·ligència artificial |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-97319-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996479368803316 |
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Barrau Thomas
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| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Artificial intelligence for financial markets : the polymodel approach / / Thomas Barrau and Raphael Douady
| Artificial intelligence for financial markets : the polymodel approach / / Thomas Barrau and Raphael Douady |
| Autore | Barrau Thomas |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (182 pages) |
| Disciplina | 332.64028563 |
| Collana | Financial Mathematics and Fintech |
| Soggetto topico |
Artificial intelligence - Financial applications
Inversions Estadística matemàtica Intel·ligència artificial |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-97319-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910574052003321 |
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Barrau Thomas
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| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence in Financial Markets : Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics / / edited by Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous, Konstantinos Theofilatos
| Artificial Intelligence in Financial Markets : Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics / / edited by Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous, Konstantinos Theofilatos |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | London : , : Palgrave Macmillan UK : , : Imprint : Palgrave Macmillan, , 2016 |
| Descrizione fisica | 1 online resource (XV, 344 p. 49 illus., 17 illus. in color.) |
| Disciplina | 658.15 |
| Collana | New Developments in Quantitative Trading and Investment |
| Soggetto topico |
Corporations—Finance
Investment banking Securities Banks and banking Risk management Economics, Mathematical Artificial intelligence - Financial applications Corporate Finance Investments and Securities Banking Risk Management Quantitative Finance Artificial Intelligence |
| ISBN | 1-137-48880-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. A Review of Applications of Artificial Intelligence in Financial Domain -- SECTION I: Financial Forecasting and Trading -- 2. Trading the FTSE100 Index – ‘Adaptive' Modelling and Optimisation Techniques -- 3. Modelling, Forecasting and Trading the Crack – A Sliding Window Approach to Training Neural Networks -- 4. GEPTrader: A new Standalone Tool for Constructing Trading Strategies with Gene Expression Programming -- SECTION II: ECONOMICS -- 5. Business Intelligence for Decision Making in Economics -- 6. An automated literature analysis on data mining applications to credit risk assessment -- SECTION III: CREDIT RISK ANALYSIS -- 7. Intelligent credit risk decision support: architecture and implementations -- 8. Artificial Intelligence for Islamic Sukuk Rating Predictions -- SECTION IV: PORTFOLIO MANAGEMENT, ANALYSIS AND OPTIMISATION -- 9. Portfolio selection as a multiperiod choice problem under uncertainty: an interation-based approach -- 10. Handling model risk in portfolio selection using a Multi-Objective Genetic Algorithm -- 11. Linear regression versus fuzzy linear regression — does it make a difference in the evaluation of the performance of mutual fund managers? |
| Record Nr. | UNINA-9910153100303321 |
| London : , : Palgrave Macmillan UK : , : Imprint : Palgrave Macmillan, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence, Learning and Computation in Economics and Finance / / Ragupathy Venkatachalam, editor
| Artificial Intelligence, Learning and Computation in Economics and Finance / / Ragupathy Venkatachalam, editor |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (331 pages) |
| Disciplina | 332.028563 |
| Collana | Understanding Complex Systems Series |
| Soggetto topico |
Artificial intelligence - Financial applications
Economics - Data processing Economia Processament de dades Intel·ligència artificial |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031152948
9783031152931 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Perspectives from the Development of Agent-based Modelling in Economics and Finance -- Towards a General Model of Financial Markets -- The U-Mart Futures Exchange Experiment and Her Institutional Design Historically Inherited -- A Bottom-Up Framework for Data-Driven Agent-Based Simulations -- Can News Networks and Topics Influence Assets Return and Volatility? -- Causal Inference and Agent-Based Models -- Finding the Human in Their Stories: Some Thoughts on Digital Humanities Tools -- Interdependence Overcomes the Limitations of Rational Theories of Collective Behavior: The Productivity of Patents by Nations -- Sand Castles and Financial Systems.-Estimation of Agent-Based Models via Approximate Bayesian Computation -- Unravelling Aspects of Decision Making Under Uncertainty -- Logic and Epistemology in Behavioral Economics -- Aggregate Investor Attention and Bitcoin Return: The Machine Learning Approach -- Information and Market Power: An Experimental Investigation into the Hayek Hypothesis -- Algorithmically Learning, Creatively and Intelligently to Play Games -- A Simonian Formalistic Perspective on Collaborative, Distributed Invention -- Modified Sraffan Schemes and Algorithmic Rational Agents. |
| Record Nr. | UNINA-9910672436903321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big data and artificial intelligence in digital finance : increasing personalization and trust in digital finance using big data and AI / / editors, John Soldatos, Dimosthenis P. Kyriazis
| Big data and artificial intelligence in digital finance : increasing personalization and trust in digital finance using big data and AI / / editors, John Soldatos, Dimosthenis P. Kyriazis |
| Autore | Soldatos John |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2022 |
| Descrizione fisica | 1 online resource : $b illustrations (some color) |
| Soggetto topico |
Artificial intelligence - Financial applications
Big data Blockchains (Databases) |
| Soggetto non controllato |
Artificial Intelligence and Big Data
Digital Finance FinTech Blockchain RegTech |
| ISBN | 3-030-94590-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Part I: Novel Big Data and AI Technologies for Digital Finance -- A Reference Architecture for Big Data Systems and AI Applications in the Finance Sector -- Hybrid Transactional and Analytical Processing for Integrated Data Management in Digital Finance and FinTech Applications -- Semantic Interoperability Modelling for Digital Finance Applications -- Semantic Streaming for Digital Finance Applications -- Part II: Blockchain Technologies and Digital Currencies for Digital Finance Applications -- Central Bank Digital Currencies and a Euro for the Future -- Efficient and Accelerated KYC Using Blockchain Technologies -- Part III: Applications of Big Data and AI in Digital Finance -- AI-based platform for Intelligent and Automated Accounting -- Addressing Intra-Day Volatility in Risk Assessments for Forex Trading -- Next-Generation Personalized Investment Recommendations -- Personalized Finance Management for Small Medium Businesses -- AML/CF supervision empowered by AI -- Analyzing Large Scale Blockchain Transaction Graphs for Fraudulent Activities -- Cybersecurity and Fraud Detection in Financial Transactions -- Part IV: Applications of Big Data and AI in Insurance -- Risk assessment for personalized health insurance products -- Alternative Data for Personalized Insurance products -- Part V: Technologies for Regulatory Compliance in the Finance Sector -- AI Governance -Trustworthy and Responsible use of AI -- Large Scale Data Anonymization for GDPR Compliance -- Conclusion. |
| Record Nr. | UNINA-9910566453103321 |
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Soldatos John
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| Cham, : Springer International Publishing AG, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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