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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…mehr
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 as the 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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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
