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Looking Back Looking Forward (LBLF)

LBLF provides a concise and analytical discussion of issues relating to the intersection of finance, technology, regulation, globalization and sustainable development.

 

Led by Professor Douglas Arner, LBLF focuses on major current issues in global finance, presenting them in their wider context.

 

Topics include digitization and datafication of finance, major trends and themes in global finance and its regulation, and the role of finance in sustainable development.

 

LBLF goes out every month to over 100,000 learners on the HKU-edX Professional Certificate in FinTech.

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The Data Race and the Shift to Multipolar Mercantilism

Looking Back Looking Forward

with Professor Douglas Arner

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In this episode, Professor Douglas Arner explores Multipolar Mercantilism, where dominant economies (U.S., China, EU, India) compete for global influence in finance, technology, and security. He emphasizes #data as a strategic asset, shaping AI, fintech, cybersecurity, and digital infrastructure.

 

While major economies leverage vast data pools, smaller economies must adopt strategic approaches to remain competitive. These include building open banking and finance ecosystems, forming regional data-sharing alliances (e.g., ASEAN), and investing in secure digital infrastructure. With rising cybersecurity threats and geopolitical tensions over data access, the future of global competition will be defined by who controls, shares, and secures data most effectively.

 

Read more about building open finance at the Oxford Business Law Blog: https://www.hkufintech.com/research

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AI in Finance: Disrupting the Industry
13:15

AI in Finance: Disrupting the Industry

In this episode of Looking Back, Looking Forward, Professor Douglas Arner explores the impact of ChatGPT and generative AI on finance. He traces the historical adoption of AI in areas such as securities trading, payments, asset management, risk management, and compliance. Factors like increased computing power, data availability, and algorithm advancements have fueled the rapid development of AI in finance. He highlights the transformative nature of ChatGPT and its ability to interface with diverse data sources, including proprietary models and institutional data. He discusses macro and micro regulatory concerns, such as the impact on employment, discrimination, and accountability. He also highlights that existing regulatory frameworks and explainability systems address these concerns, ensuring transparency and responsibility. Data and human rights laws, like GDPR, also influence AI use in finance. Despite challenges, Professor Arner underscores the immense transformative potential of generative AI systems in finance as well as the maximum value people can get from data and analytics. Further Reading: Artificial Intelligence in Finance: Challenges, Opportunities and Regulatory Developments edited by Nydia Remolina and Aurelio Gurrea-Martinez - https://www.amazon.com/Artificial-Intelligence-Finance-Opportunities-Developments/dp/1803926163 Topic Guide: 0:00 Introduction 0:19 ChatGPT and Generative AI in Finance 1:20 Securities Trading: Automation and AI in Action 3:17 Payments and Fraud: Enhancing Security and Efficiency 4:15 Asset Management: The Rise of Robo Advisory Services 4:49 Risk Management, Compliance, and More: AI Applications in Finance 6:18 Factors Driving AI Development in Financial Services 7:39 The Transformative Power of ChatGPT in Finance 9:57 Macro and Micro Regulatory Considerations 11:14 The Role of Explainability Systems in Addressing Concerns
LBLF Season 3
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