Al Naqvi - Artificial Intelligence for Asset Management and Investment

1 Cover

2 Title Page Artificial Intelligence for Asset Management and Investment A Strategic Perspective AL NAQVI

3 Copyright

4 Dedication

5 Preface

6 Acknowledgments

7 Chapter 1: AI in Investment Management WHAT ABOUT AI SUPPLIERS? LISTENING WITHOUT JUDGING THE FOUR STAGES OF AI IN INVESTMENTS THE CORE MODEL OF AIAI YOUR JOURNEY THROUGH THIS BOOK HOW TO READ AND APPLY THIS BOOK? REFERENCES

8 Chapter 2: AI and Business Strategy WHY STRATEGY? THE RED BUTTON AI—A REVOLUTION OF ITS OWN INTELLIGENCE AS A COMPETITIVE ADVANTAGE INTELLIGENCE AS A COMPETITIVE ADVANTAGE AND VARIOUS STRATEGY SCHOOLS THE INTELLIGENCE SCHOOL INTELLIGENCE AND ACTIONS ACTIONS AUTOMATION INTELLIGENCE ACTION CHAIN AND SEQUENCE ENTERPRISE SOFTWARE DATA COMPETITIVE ADVANTAGE BUSINESS CAPABILITIES

9 Chapter 3: Design WHO IS RESPONSIBLE FOR DESIGN? INTRODUCTION TO DESIGN AI AS A COMPETITIVE ADVANTAGE THE TEN ELEMENTS OF DESIGN 1. DESIGN YOUR BUSINESS MODEL 2. SET GOALS FOR THE ENTIRE FIRM 3. SPECIFY OBJECTIVES FOR AUTOMATION AND INTELLIGENCE 4. DESIGN WORK TASK FRAMES BASED ON HUMAN-COMPUTER INTERACTION 5. PERFORM A DTC (DO, THINK, CREATE) ANALYSIS 6. CREATE A SADAL FRAMEWORK 7. DEPLOY A FEEDBACK SYSTEM AND DEFINE PERFORMANCE MEASURES 8. DETERMINE THE BUSINESS CASE OR VALUE 9. ANALYZE RISKS 10. DEVELOP A GOVERNANCE PLAN SOME ADDITIONAL IDEAS ABOUT DESIGNING INTELLECTUALIZATION SUMMARY OF THE DESIGN PROCESS REFERENCES NOTE

10 Chapter 4: Data WHO IS RESPONSIBLE FOR THE DATA CAPABILITY? DATA AND MACHINE LEARNING RAW DATA STRUCTURED VS. UNSTRUCTURED DATA DATA USED IN INVESTMENTS DATA MANAGEMENT FUNCTION FOR THE AI ERA STEP 1: DATA NEEDS ASSESSMENT (DNA) STEP 2: PERFORM STRATEGIC DATA PLANNING STEP 3: KNOW THE SENSORS AND SOURCES (IDENTIFY GAPS) STEP 4: PROCURE AND UNDERSTAND THE SUPPLY BASE STEP 5: UNDERSTAND THE DATA TYPE (SIGNALS) STEP 6: ORGANIZE DATA FOR USABILITY STEP 7: ARCHITECT DATA STEP 8: ENSURE DATA QUALITY STEP 9: DATA STORAGE AND WAREHOUSING STEP 10: EXCEL IN DATA SECURITY AND PRIVACY STEP 11: IMPLEMENT DATA FOR AI STEP 12: PROVIDE INVESTMENT SPECIALIZATION ABOUT LEGACY DATA MANAGEMENT REFERENCES

11 Chapter 5: Model Development WHO IS RESPONSIBLE? HIGH-LEVEL PROCESS MODELS THE POWER OF PATTERNS TECHNIQUES OF LEARNING WHAT IS MACHINE LEARNING? SCIENTIFIC PROCESS ON STEROIDS THE LEARNING MACHINES ALGORITHMS SUPERVISED LEARNING SUPERVISED: CLASSIFICATION CLASSIFICATION: RANDOM FOREST CLASSIFICATION: USING MATHEMATICAL FUNCTIONS CLASSIFICATION: SIMPLE LINEAR CLASSIFIER SUPERVISED: SUPPORT VECTOR MACHINE CLASSIFICATION: NAIVE BAYES CLASSIFICATION: BAYESIAN BELIEF NETWORKS CLASSIFICATION: K-NEAREST NEIGHBOR SUPERVISED: REGRESSION SUPERVISED: MULTIDIMENSIONAL REGRESSION UNSUPERVISED LEARNING NEURAL NETWORKS REINFORCEMENT LEARNING REFERENCES

12 Chapter 6: Evaluation WHO PERFORMS THE EVALUATION? PROBLEMS MAKING THE MODEL WORK OVERFITTING AND UNDERFITTING SCALE AND MACHINE LEARNING NEW METHODS BIAS AND VARIANCE BACKTESTING BACKTESTING PROTOCOL REFERENCES

13 Chapter 7: Deployment REFERENCE ARCHITECTURE THE REFERENCE ARCHITECTURE AND HARDWARE REFERENCES

14 Chapter 8: Performance WHO IS RESPONSIBLE FOR PERFORMANCE? WHAT ARE THE WORK PROCESSES OF PERFORMANCE? BUSINESS PERFORMANCE TECHNOLOGICAL PERFORMANCE REFERENCES

15 Chapter 9: A New Beginning BUILDING AN INVESTMENT MANAGEMENT FIRM AROUND ARTIFICIAL INTELLIGENCE? THE FALLACY OF GOING DIGITAL WHY BUILD YOUR FIRM AROUND AI? YOU MUST RELY ON YOUR OWN CAPABILITIES WHAT IS ASSET SCIENCE? A HEALTHY CYCLE THE TOOL SET THIS IS NOT JUST AUTOMATION REFERENCES

16 Chapter 10: Customer Experience Science CUSTOMER EXPERIENCE VALUE, STRENGTH, AND DURATION OF RELATIONSHIP UNDERSTANDING CUSTOMERS: EMPATHY FOR CX STEPS TO BECOME AN EMPATHETIC ASSET MANAGEMENT FIRM KNOW YOUR EMPMETER EXPAND EMPATHY AWARENESS AND UNDERSTANDING INCORPORATE INTO PRODUCTS AND SERVICES WHAT IS AUTOMATED EMPATHY AND COMPASSION (AEC)? INCORPORATING AEC MARKETING REFERENCES

17 Chapter 11: Marketing Science WHO UNDERTAKES THIS RESPONSIBILITY? HOW TO APPLY AI FOR MARKETING BEGIN WITH ASSESSMENT KNOW YOUR DATA THE AI PLAN FOR ASSET MANAGEMENT MARKETING PERFORM STRATEGIC PLANNING MANAGE PRODUCT PORTFOLIO WITH AI TRANSFORM YOUR COMMUNICATIONS BUILD RELATIONSHIPS EXECUTE WITH EXCELLENCE REFERENCES

18 Chapter 12: Land that Institutional Investor with AI WHO IS RESPONSIBLE FOR IRMS AUTOMATION? IS IRMS YOUR CRM SYSTEM? KNOW THYSELF: AUTOMATED SELF-DISCOVERY AUTOMATED ASSET CLASS ANALYSIS AUTOMATED INSTITUTIONAL ANALYSIS AUTOMATED STRUCTURE AND TERMS ANALYSIS AUTOMATED FEE ANALYSIS AUTOMATED COMMUNICATIONS UNLEASH THE POWER OF KNOWING

19 Chapter 13: Sales Science WHAT IS SALES SCIENCE? WHO IS RESPONSIBLE FOR IMPLEMENTING SALES SCIENCE? ARE YOU DRIVING THIS IN SALES? HOW TO BUILD YOUR AI-BASED SALES SYSTEM REFERENCES

20 Chapter 14: Investment: Managing the Returns Loop WHO IS RESPONSIBLE FOR INVESTMENT MANAGEMENT? HOW TO APPROACH BUILDING THE NEW-ERA INVESTMENT FUNCTION? THE CORE TOOL SET WHAT WILL BE THE FUNCTION OF YOUR INVESTMENT LAB? MAKE THE DECISIONS A NEW WORLD THE (UNNECESSARY) DEBATE MORE BEHAVIORS RESEARCH AND INVESTMENT STRATEGY PORTFOLIO PERFORMANCE REFERENCES

21 Chapter 15: Regulatory Compliance and Operations WHO IS RESPONSIBLE? REGULATORY COMPLIANCE WHY INTELLIGENT AUTOMATION? HAVE YOU SCOPED OUT WHAT TO DO? HOW TO DO IT? HOW TO USE TECHNOLOGY FOR GIPS IMPLEMENTATION? BACK AND MIDDLE OFFICE

22 Chapter 16: Supply Chain Science WHO IS RESPONSIBLE FOR SUPPLY CHAIN SCIENCE? HOW TO THINK ABOUT SUPPLY CHAINS REFERENCES

23 Chapter 17: Corporate Social Responsibility CSR WOES: CAN PROCESSES EXPLAIN THEM? WHAT ARE THE CRITICISMS OF CSR? MEASUREMENT ISSUES BEHAVIORAL AND ROLE ISSUES STRATEGIC AND ORGANIZATIONAL ISSUES HOW TO APPLY AI IN CSR? CSR MUST NOT BE FORGOTTEN ESG INVESTMENT HOW CAN AI HELP? YOU MUST AVOID THESE MISTAKES SUMMARY STEPS REFERENCES

24 Chapter 18: AI Organization and Project Management THE NEW ASSET MANAGEMENT ORGANIZATION WHY A CAIO/COO ROLE? WHAT IS CHANGING? HOW TO GET THERE? ISSUES OF THE NEW ORGANIZATION CHANGE MANAGEMENT MANAGING AI PROJECTS REFERENCES

25 Chapter 19: Governance and Ethics CORPORATE GOVERNANCE WITH AI GOVERNANCE OF AI FRAMING THE ETHICAL PROBLEMS FROM A PRAGMATIC VIEWPOINT SOME OBVIOUS ETHICAL ISSUES HUMANS AND AI ETHICS CHARTER REFERENCES

26 Chapter 20: Adaptation and Emergence THE REVOLUTION IS REAL COMPLEX ADAPTIVE SYSTEMS OUR CORONAVIRUS MELTDOWN PREDICTION

27 Index

28 End User License Agreement

1 Chapter 3 TABLE 3.1 SADAL in a Work Task

2 Chapter 5TABLE 5.1 Methods Used in Finance Applications (adopted from research by Andr...

3 Chapter 14TABLE 14.1 Applications in Finance

1 Chapter 1 FIGURE 1.1 The AIAI Core Model

2 Chapter 3 FIGURE 3.1 DTC ModelFIGURE 3.4 The Design Process

3 Chapter 5FIGURE 5.1 Data, Features, and TargetFIGURE 5.2 The Process of Using Examples in Supervised LearningFIGURE 5.3 Function Based SplitFIGURE 5.4 Predicting VotingFIGURE 5.5 Solution Space, Many Lines PossibleFIGURE 5.6 Support Vector MachineFIGURE 5.7 Non-SeparableFIGURE 5.8 InseparableFIGURE 5.9 Inseparable Separated via TransformationFIGURE 5.10 k-Nearest NeighborFIGURE 5.11 Finding the FunctionFIGURE 5.12 PlotFIGURE 5.13 Random Placement of a LineFIGURE 5.14 Adding LinesFIGURE 5.15 Finding the Best-Fit LineFIGURE 5.16 Step 1 of Clustering k-MeansFIGURE 5.17 k-Means Clustering Step 2FIGURE 5.18 Step 3 k-Mean ClusteringFIGURE 5.19 Step 4 k-Mean ClusteringFIGURE 5.20 Using a Neural Network to PredictFIGURE 5.21 How a Neuron Passes the Output to the Next LayerFIGURE 5.22 Deep Learning

4 Chapter 6FIGURE 6.1 Roles in the Evaluation FunctionFIGURE 6.2 Train, Validate, Test

5 Chapter 7FIGURE 7.1 Reference Architecture