| Description |
1 online resource (179 p.) |
| Series |
Innovations in Big Data and Machine Learning Series |
|
Innovations in Big Data and Machine Learning Series
|
| Contents |
Intro -- Half Title -- Series Page -- Title Page -- Copyright Page -- Dedication -- Contents -- Editor Biographies -- Contributors -- Foreword -- Preface -- 1. Big Data and Artificial Intelligence for Financial Inclusion: Benefits and Issues -- 1.1 Introduction -- 1.2 Literature Review -- 1.3 How AI Can Help Expand Access to Banking Services/Financial Inclusion -- 1.3.1 Big Data and Data Analytics Advantages for Financial Inclusion -- 1.3.1.1 Big Data Facilitates the Creation of Credit Scores for the Excluded Population |
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1.3.1.2 Big Data Enables Financial Services Companies to More Effectively Manage Credit Risk -- 1.3.1.3 Greater Identity Solutions Are Offered by Big Data Considerably More Effectively Than by Know-Your-Customer (KYC) Regulations -- 1.3.1.4 Improved Marketing of Financial Services -- 1.3.1.5 Big Data Can provide inputs that Help Policies and Strategies for Financial Inclusion -- 1.3.2 Additional Advantages of AI in the Financial Inclusion Sector -- 1.3.2.1 AI Can Make It Easier for Adults without Bank Accounts to Open Accounts |
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1.3.2.2 AI Models Can Provide Customers with Smart and Individualized Financial Goods and Services -- 1.3.2.3 AI Will Enhance Communication and Customer Service -- 1.3.2.4 AI Will Assist in Reducing Fraud -- 1.3.2.5 AI Helps Establish a Credit History -- 1.4 A Few Problems -- 1.4.1 AI Might Keep Weak People Out of the Financial System -- 1.4.2 Unconscious Bias Is Incorporated into the Creation of AI Tools, Models, and Applications -- 1.4.3 Job Losses or Employment Transfers -- 1.4.4 The Fear of Entrusting AI Systems with Decision-Making |
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1.4.5 AI Algorithms Might Not Have Been Adequately Trained with Data -- 1.4.6 Lack of Skilled AI Employees -- 1.4.7 The Board's Approval for the AI's Inclusion in Operational Procedures Is Not Guaranteed -- 1.4.8 Handling Inaccurate Data Is a Problem -- 1.4.9 Privacy and Security Concerns with Client Data -- 1.5 Conclusion -- References -- 2. The Contribution of AI-Based Analysis and Rating Models to Financial Inclusion: The Lenddo Case for Women-Led SMEs in Developing Countries -- 2.1 Introduction -- 2.1.1 Review of Literature: AI and Creditworthiness Analysis |
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2.1.1.1 AI and Productivity Gains in Credit Analysis and Scoring Procedures -- 2.1.1.2 The Contribution of Big Data to the AI Process for Credit Analysis -- 2.1.1.3 The Socio-economic Impact of AI in Strengthening Inclusion -- 2.1.2 The Research Methodology of Case Study: Lenddo's Universal Credit -- 2.1.3 The Limits of the IA Approach for Credit Analysis -- 2.2 Conclusion -- Notes -- References -- 3. Is the Capital Market Based on Blockchain Technology Efficient for Financial Inclusion? -- 3.1 Introduction -- 3.2 Conceptual and Theoretical Framework |
| Summary |
This book covers Big Data, Machine Learning, and Artificial Intelligences related technologies and how these technologies can enable design, development, and delivery of customer-focused financial services to both corporate and retail customers and how to extend the benefits to the financially excluded sections of society |
| Notes |
Description based upon print version of record |
|
3.2.1 The Influence of Fintech and Blockchain Technology on the Capital Market Efficiency |
| Subject |
Finance -- Technological innovations
|
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Financial services industry -- Technological innovations
|
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Artificial intelligence -- Economic aspects
|
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Artificial intelligence -- Economic aspects
|
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Finance -- Technological innovations
|
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Financial services industry -- Technological innovations
|
| Form |
Electronic book
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| Author |
Assadi, Djamchid
|
|
Starnawska, Marzena
|
| ISBN |
9781003804659 |
|
1003804659 |
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