AI and the future of banking / Tony Boobier.
By: Boobier, Tony
Language: English Series: Wiley finance editionsPublisher: Chichester, West Sussex, United Kingdom : John Wiley & Sons Ltd, 2020Description: 1 online resource (xx, 283 pages) : illustrationsContent type: text Media type: computer Carrier type: online resourceISBN: 9781119596165Subject(s): Banks and banking -- Technological innovations | Artificial intelligence -- Industrial applications | Business and economics -- Banks and bankingGenre/Form: Electronic books.DDC classification: 332.1028563 Online resources: Full text available at Wiley Online Library Click here to view| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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COLLEGE LIBRARY | COLLEGE LIBRARY | 332.1028563 B64417 2020 (Browse shelf) | Available | CL-50794 |
ABOUT THE AUTHOR
TONY BOOBIER is a former IBM worldwide executive focusing on financial services. He has over 30 years of experience and is a frequent writer and international public speaker. Tony possesses a deep understanding of how to apply business intelligence and analytics to enhance the management and delivery of products and services in numerous industries. A recognised expert in customer analytics, risk and operational effectiveness, he is a strong advocate for enterprise-wide analytics to improve service and reduce cost. He holds professional qualifications in engineering, marketing, supply chain management and insurance.
Includes bibliographical references and index.
TABLE OF CONTENTS
Acknowledgements xv
About the Author xvi
Introduction xvii
Chapter 1 Prologue: Why Banking? 1
Summary 1
Introduction 2
What is Banking? 4
What Do We Mean by ‘Money’ Today? 7
A Cashless Society Increasingly Emerges 8
Key Banking Functions 10
Future Jobs in Banking 14
Conclusion 17
References 18
Chapter 2 Imperatives in Banking 21
Summary 21
Introduction 21
Strategy and Imperatives 23
Strategy 23
Business Imperatives 24
Current Imperatives in Banking 24
Comparable Imperatives in the Retail Industry 26
Comparable Imperatives in the Telecom Industry 27
Comparable Imperatives in the Healthcare Industry 29
Future Imperatives in Banking 30
Greater Customer Centricity 30
Becoming Truly Digital 31
Completely Accepting Technological Change 33
Reimagining Banking 33
Reinventing Risk Management 35
Conclusion 36
References 37
Chapter 3 Data and Analytics Primer 39
Summary 39
Introduction 39
Data Management and Analytics 42
Data Management 42
The Hierarchy of Analytics 43
‘Next-Generation’ Cognitive Analytics 45
Extracting Value from Data 46
The Importance of Location Analytics 50
Conclusion 51
References 52
Chapter 4 Key Elements of Banking Analytics 55
Summary 55
Introduction 56
Office of Finance Management 56
Performance Management and Integrated Decision Making 58
The Key Elements of Banking Performance Management 59
Customer Analytics 61
Customer Insight 61
Credit Ratings 65
Branch-Specific Campaigns 66
Impact of Social Media Campaigns 67
Relationship Pricing 69
Client Servicing 71
Risk Management 73
Risk Scenario Analytics 74
Fraud Detection 75
Regulatory Compliance 76
Risk Management and AI 76
Operational Efficiency 77
IT Cost Transparency 78
Branch Performance Management 78
Contact Centre Service 80
Payments Monitoring 82
Mortgage Tracking 83
Sales, Compensation and Commission Management 83
Financial Markets Risk and Trade Monitoring 84
Analytics in Portfolio Management 85
Derivative Markets 86
Conclusion 87
References 89
Chapter 5 Machine Learning, AI and ‘Apps’ 93
Summary 93
Introduction 93
Theory and Practice of Machine Learning 95
Apps and Their Usage 96
Data Visualisation 101
Voice Recognition and Voice Assistants 102
Visual and Facial Recognition 104
Thumbprint Recognition 106
Palm Vein Recognition 107
Wealth Management Systems and Apps 107
The Biometric Moral Argument 109
Conclusion 111
References 112
Chapter 6 AI and the Importance of Brand in Banking 115
Summary 115
Introduction 116
Brand Value and Equity in Banking 117
Millennial and Gen Y Brand Expectations from Bank Brands 119
Branding Expectations of Generation Z 120
Branding Expectations of Generation X 121
Branding and Customer Experience Interlocked 123
Branding and Human-Centred Design 124
To Brand or to Debrand? 125
Banks Will Use AI to Become Lifestyle Managers 128
Consumption and Credit Smoothing 128
Conclusion 130
References 130
Chapter 7 AI Leadership and Employee Transformation 133
Summary 133
Introduction 133
Leadership in an AI-Infused Age 136
Augmented Leadership 137
Analytically Infused Leadership 138
A New Approach to Leadership: ‘Trust but Verify’ 140
Attributes of AI-Infused Leaders 141
Leadership Training for the Future 143
‘Digital Future of Banking Requires a New Leadership Model’ 145
Zen and Leadership in Banking 146
Functional Change and Role Transformation 147
The Evolution of the Banking Employee 149
A Banking Employee Persona in 2050 149
Conclusion 151
References 152
Chapter 8 The Bank of the Future 155
Summary 155
Introduction 156
Branch Makeover 156
The Emergence of the Café Bank 159
Millennials Not Happy with Dealing Only with Robots 160
Virtual Reality: Banking and Gaming Converge 161
Universal Banking and Beyond 163
Universal Banking in the United States 164
Banks as the Catalyst for Change: ‘Peer to Peer’ 164
Payment Processes Become More Customer Centric 166
Five Scenarios for the ‘Bank of the Future’ 167
The Full-Service Bank 168
The Digital Bank 169
The Disaggregated Bank 170
The Conversational Bank 173
The Collaborative Bank 174
Transformation of the Investment Bank 175
Conclusion 178
References 179
Chapter 9 Open Banking and Blockchain 183
Summary 183
Introduction 184
Setting the Stage: Open Banking 184
Interlock between AI and Open Banking 186
Blockchain: Setting the Stage 186
Interlock between Blockchain and AI 188
Blockchain in Banking 188
Interbank Market 189
Forex Market 190
Investment Banks and Blockchain 191
Blockchain in Indian Banking 193
Blockchain and Open Banking in Africa 196
Conclusion 199
References 201
Chapter 10 Innovation and Implementation 203
Summary 203
Introduction 203
New Roles and Responsibilities 204
Bootcamps, Hackathons, Innovation Labs, and Other Devices 205
Implementation 207
Innovation or Adaptation? 208
The Use of ‘Design Thinking’ 210
Finding Capital to Innovate: One Example 211
Fintech for Banking 212
Blockages to Innovation 216
Conclusion 218
References 218
Chapter 11 Cybercrime and IT Resilience 221
Summary 221
Introduction 222
Cybercrime in the Context of Operational Risk 224
The Internationalisation of Cybercrime 225
Cyber Security Toolkits 226
Cyber Risk Management Apps 227
Broader Cyber Issues for Banking 227
Safeguarding the Bank of the Future: New Cyber Security Threats 228
Responding to Cyber Attack 230
Cyber Readiness 231
New Cyber Roles, New Cyber Responsibilities 233
AI Fraud Detection in Banking 234
Advanced Analytics in Fraud Detection 235
AI and Anomaly Detection 236
Fraudulent Use of Data 236
Cyber and the Law 238
Conclusion 239
References 239
Chapter 12 Epilogue 243
Appendix: Fintech in Banking 247
Index 271
Summary"AI and the Future of Banking is an informative guide on the applications of Cognitive Analytics/Artificial Intelligence (AI) to the banking industry. The book will equip any industry participant, including new entrants to the industry, with the essential information to understand the implications of data and analytics on their roles, responsibilities and personal career development, with focus on the use of analytics to create operational effectiveness, customer retention and finance and risk management. While a combination of theory and published case studies, it will not be a technical book (i.e. about IT architecture, platforms and algorithms) or a detailed review of a specific working area but rather an easy read for those with limited or no IT background. The book will also discuss the concept of data-driven 'Open Banking, ' which is a process that uses 'APIs' to share information securely, without having to reveal passwords. IDC say that by 2020, 50% of all businesses will be using cognitive analytics, which are intelligent and self-learning systems that respond to human voices rather than needing to be 'coded'. The use of Cognitive Analytics/Artificial Intelligence (AI) Systems and data in banking is set to accelerate. The cognitive or a 'AI' computing market is estimated to exceed $12.0 Billion by 2022, with banking identified as an 'early-mover' industry. Gartner say that AI will be mainstream for banking in 5-10 years. There is already evidence that early-mover banks are beginning to investigate these new technologies. However, there are many laggards and market maturity is inconsistent, with knowledge transfer being critical at this stage"-- Provided by publisher
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