Introduction

This workshop will be an in-person event at PAKDD 2026, taking place in June, 2026 in Hong Kong, China. The session will cover invited keynote talks, paper presentation, and a panel discussion. Advancements in AI and data science are fundamentally reshaping the digital finance landscape, offering unprecedented opportunities to enhance financial services, improve risk assessment, enable real-time fraud detection, and support regulatory compliance. The rapid growth of digital finance, including cryptocurrencies, DeFi, blockchain, and AI-driven financial services, has revolutionized the way individuals, companies, and societies interact with financial systems. In particular, machine learning, deep learning, and large language models have significant potential to transform how financial data is analyzed, processed, and utilized across domains such as blockchain analytics, decentralized finance, algorithmic trading, digital asset management, and financial risk modeling. This intersection of AI and digital finance enables powerful new capabilities such as real-time risk analytics and fraud prevention, personalized financial services at scale, enhanced regulatory compliance through RegTech and SupTech, improved market surveillance and anomaly detection, as well as greater financial inclusion and micro-lending opportunities. The workshop aims to bring together researchers, practitioners, industry experts, and policymakers interested in the development and application of AI and data science in digital finance. It will foster interdisciplinary dialogue on how these technologies are transforming traditional banking, payment systems, and investment management, and creating new paradigms in decentralized finance and digital currencies.

The workshop’s theme is AI and Data Science for Digital Finance: Transforming Markets, Assets, and Inclusion. We invite contributions that explore the development and application of AI, machine learning (ML), deep learning, large language models (LLMs), network analysis, and advanced data science methods in digital finance and financial services. Topics of interest include, but are not limited to:  

• Fraud Detection, Risk, and Compliance

• Market Analysis and Investment

• Blockchain and Digital Assets  

• Multimodal Financial Data Analysis

• Financial Inclusion and Sustainability  

• Emerging Technologies and Challenges  

Keynote Speakers (TBD)

Organizing Committee

Stephen Chan (American University of Sharjah, UAE)

Yuanyuan Zhang (University of Manchester, UK)

Jeffrey Chu (Renmin University of China, China)

Zihao Wang (University of Tennessee at Chattanooga, USA)

Shujie Ma (University of California Riverside, USA)

Zhangyang Wang (University of Texas at Austin, USA)

Yulia R. Gel (Virginia Tech, USA)

Qingsong Wen (Squirrel Ai Learning, USA)

Yuzhou Chen (University of California Riverside, USA)

 Program Committee (TBD)