ICFT 2024

The 5th International Conference on Financial Technology (ICFT 2024)

The 5th International Conference on Financial Technology successfully concluded on September 24, 2024, in Singapore. The event received strong support from leading institutions, including the National University of Singapore, Nanyang Technological University, Singapore Management University, and Shanghai Jiao Tong University. It brought together experts, scholars, and industry representatives from China, Singapore, France, Italy, Thailand, the UAE, and Malaysia to discuss the latest trends, innovations, and challenges in financial technology.
With a focus on “Financial Technology,” the conference featured keynote speeches, oral presentations, and poster sessions. Participants shared cutting-edge research and practical applications in areas such as AI, machine learning, the metaverse, and large language models, sparking engaging discussions among attendees.

ICFT 2024 Conference Proceedings
ICFT 2024 received submissions from researchers in over 20 countries within the field. Following a rigorous peer-review process, all accepted papers were published by Springer in the prestigious Communications in Computer and Information Science series (CCIS, volume 2437; ISSN: 1865-0929). The proceedings have also been successfully indexed in EI Compendex, Scopus, and other leading academic databases.


Group Photo-ICFT 2024

Opening Speech

Prof. Ke-Wei Huang delivered the opening speech, expressing gratitude to the speakers, participants. He highlighted the rapid development of financial technology and the critical role of interdisciplinary collaboration in driving innovation. Prof. Huang emphasized the transformative impact of technologies such as AI, machine learning, and blockchain on the financial sector, urging attendees to engage in discussions that will shape the future of the industry.

Keynote Speech Session 1

Prof. Erik Cambria, Nanyang Technological University, Singapore
Speech Title: Explainable AI for Fully Interpretable Financial Insights
Prof. Erik Cambria discussed the importance of explainable artificial intelligence (XAI) in the financial sector, emphasizing how transparency plays a crucial role in decision-making. He demonstrated how XAI techniques can make complex financial models more transparent, enabling decision-makers to better understand the logic behind the data. His research shows that improving explainability not only enhances trust but also effectively reduces risks, providing financial institutions with deeper, more insightful analyses.

Keynote Speech Session 1

Prof. SIAU Keng Leng, Singapore Management University, Singapore
Speech Title: AI and Metaverse: The Good, The Bad, and The Unknown
 Prof. SIAU Keng Leng explored the three facets of artificial intelligence (AI) and the metaverse: the positive aspects, the negative concerns, and the unknown implications. He highlighted the benefits, such as enhanced user experiences and the potential for driving innovation. On the flip side, he discussed the challenges, including privacy risks and algorithmic biases. The "unknown" aspect focused on the complex and evolving impact of these technologies on society's future. In his lecture, Prof. Siau called for interdisciplinary collaboration and robust policy frameworks to ensure the responsible development of AI and the metaverse.

Invited Speech Session

Dr. Thierry H. Brutman, EDDA Stock, Finance
Lecture Title: AI & Options: Unlocking the Potential of a Self-Managed Company through New Knowledge Management, including Machine Learning & Blockchain
 Dr. Thierry H. Brutman discussed how new knowledge management techniques, including machine learning and blockchain, can unlock the potential of self-managed companies. He emphasized the role of AI in optimizing decision-making and improving efficiency, highlighting how these technologies can enhance a company’s flexibility and innovation. Dr. Brutman also explored the strategies for implementing such transformations, as well as the challenges companies may face in adopting these advanced tools.


Assoc. Prof. Ke-Wei Huang, National University of Singapore, Singapore
Lecture Title: Advancing Industry Classification: From Traditional Methods to AI-Powered Approaches with Large Language Models
Assoc. Prof. Ke-Wei Huang focused on the advancements in industry classification, comparing traditional methods with AI-driven approaches, particularly large language models. He highlighted how AI enhances both the accuracy and efficiency of classification, enabling the processing of complex data patterns that help businesses better understand market dynamics. Prof. Huang also discussed the challenges of implementing these new methods and the potential impact they could have on various industries.


Prof. Jaber Jemai, Higher Colleges of Technology, UAE
Lecture Title: Financial Advising: AI and ML Leverage
Prof. Jaber Jemai explored how artificial intelligence (AI) and machine learning (ML) can enhance the effectiveness of financial advising. He introduced the applications of AI and ML in data analysis, risk assessment, and client relationship management, emphasizing how these technologies enable advisors to offer personalized financial advice. Prof. Jemai also discussed the challenges of implementing these technologies and highlighted future trends and opportunities in the field of financial advising.


Prof. Steven Li, Royal Melbourne Institute of Technology, Australia
Speech Title: "Do Investor Protection Measures Matter for Equity Crowdfunding Portals?"
Prof. Steven Li discussed the importance of investor protection measures on equity crowdfunding platforms. He explored how these measures influence investor trust and participation, and evaluated their impact on the success rate of fundraising. The lecture also highlighted the variations in the implementation of protection measures across different countries and regions, as well as potential avenues for future improvements.


Prof. Chi Seng Pun, Nanyang Technological University, Singapore
Speech Title: "Distributional Reinforcement Learning and Cumulative Prospect Theory"
Prof. Chi Seng Pun explored the integration of distributional reinforcement learning with cumulative prospect theory. He discussed how the framework of distributional reinforcement learning can be applied to decision-making processes to better understand and predict risks and rewards. He also explained how cumulative prospect theory offers a more behaviorally accurate model for decision-makers, emphasizing the potential applications of this integration in fields like finance, gaming, and others. He highlighted the value of this combination in improving decision quality.