Al Naqvi

Artificial Intelligence for Asset Management and Investment

A Strategic Perspective

• Gebundenes Buch

Produktbeschreibung

Make AI technology the backbone of your organization to compete in the Fintech era

The rise of artificial intelligence is nothing short of a technological revolution. AI is poised to completely transform asset management and investment banking, yet its current application within the financial sector is limited and fragmented. Existing AI implementations tend to solve very narrow business issues, rather than serving as a powerful tech framework for next-generation finance. Artificial Intelligence for Asset Management and Investment provides a strategic viewpoint on how AI can be comprehensively integrated within investment finance, leading to evolved performance in compliance, management, customer service, and beyond.

No other book on the market takes such a wide-ranging approach to using AI in asset management. With this guide, you'll be able to build an asset management firm from the ground up--or revolutionize your existing firm--using artificial intelligence asthe cornerstone and foundation. This is a must, because AI is quickly growing to be the single competitive factor for financial firms. With better AI comes better results. If you aren't integrating AI in the strategic DNA of your firm, you're at risk of being left behind.
_ See how artificial intelligence can form the cornerstone of an integrated, strategic asset management framework
_ Learn how to build AI into your organization to remain competitive in the world of Fintech
_ Go beyond siloed AI implementations to reap even greater benefits
_ Understand and overcome the governance and leadership challenges inherent in AI strategy

Until now, it has been prohibitively difficult to map the high-tech world of AI onto complex and ever-changing financial markets. Artificial Intelligence for Asset Management and Investment makes this difficulty a thing of the past, providing you with a professional and accessible framework for setting up and running artificial intelligence in your financial operations.

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Produktdetails

• Wiley Finance Editions
• Verlag: Wiley / Wiley & Sons
• Artikelnr. des Verlages: 1W119601820
• 1. Auflage
• Seitenzahl: 320
• Erscheinungstermin: 9. Februar 2021
• Englisch
• Abmessung: 236mm x 158mm x 32mm
• Gewicht: 531g
• ISBN-13: 9781119601821
• ISBN-10: 1119601827
• Artikelnr.: 58304678

Autorenporträt

AL NAQVI is the CEO of the American Institute of Artificial Intelligence, where he designs and develops machine learning based finance products, teaches classes on applied AI, deep learning, and cognitive transformation, and leads the company strategy. He studies the application of deep learning to financial engineering, investment, and asset management. He is also the author of Artificial Intelligence for Audit, Forensic Accounting, and Valuation (Wiley).

Inhaltsangabe

Preface xv

Acknowledgments xxi

Chapter 1: AI in Investment Management 1

What about AI Suppliers? 5

Listening without Judging 6

The Four Stages of AI in Investments 9

The Core Model of AIAI 14

Your Journey through This Book 16

How to Read and Apply this Book? 16

References 17

Chapter 2: AI and Business Strategy 19

Why Strategy? The Red Button 19

AI--a Revolution of its Own 21

Intelligence as a Competitive Advantage 22

Intelligence as a Competitive Advantage and Various Strategy Schools 23

The Intelligence School 25

Intelligence and Actions 26

Actions 27

Automation 28

Intelligence Action Chain and Sequence 28

Enterprise Software 29

Data 29

Competitive Advantage 30

Business Capabilities 31

Chapter 3: Design 35

Who Is Responsible for Design? 36

Introduction to Design 36

AI as a Competitive Advantage 38

The Ten Elements of Design 40

1. Design Your Business Model 41

2. Set Goals for the Entire Firm 44

3. Specify Objectives for Automation and Intelligence 45

4. Design Work Task Frames Based on Human-Computer Interaction 45

5. Perform a DTC (Do, Think, Create) Analysis 46

6. Create a SADAL Framework 47

7. Deploy a Feedback System and Define Performance Measures 49

8. Determine the Business Case or Value 49

9. Analyze Risks 50

10. Develop a Governance Plan 50

Some Additional Ideas about Designing Intellectualization 50

Summary of the Design Process 51

References 52

Chapter 4: Data 53

Who Is Responsible for the Data Capability? 53

Data and Machine Learning 55

Raw Data 55

Structured vs. Unstructured Data 56

Data Used in Investments 57

Data Management Function for the AI Era 58

Step 1: Data Needs Assessment (DNA) 59

Step 2: Perform Strategic Data Planning 59

Step 3: Know the Sensors and Sources (Identify Gaps) 61

Step 4: Procure and Understand the Supply Base 61

Step 5: Understand the Data Type (Signals) 62

Step 6: Organize Data for Usability 62

Step 7: Architect Data 63

Step 8: Ensure Data Quality 63

Step 9: Data Storage and Warehousing 63

Step 10: Excel in Data Security and Privacy 63

Step 11: Implement Data for AI 64

Step 12: Provide Investment Specialization 65

About Legacy Data Management 66

References 67

Chapter 5: Model Development 69

Who Is Responsible? 69

High-Level Process 70

Models 73

The Power of Patterns 74

Techniques of Learning 75

What Is Machine Learning? 76

Scientific Process on Steroids 79

The Learning Machines 79

Algorithms 80

Supervised Learning 82

Supervised: Classification 85

Classification: Random Forest 86

Classification: Using Mathematical Functions 87

Classification: Simple Linear Classifier 88

Supervised: Support Vector Machine 91

Classification: Naive Bayes 94

Classification: Bayesian Belief Networks 95

Classification: k-Nearest Neighbor 95

Supervised: Regression 96

Supervised: Multidimensional Regression 99

Unsupervised Learning 100

Neural Networks 103

Reinforcement Learning 106

References 107
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