Abstract: FDT-AI is researching and implementing how to leverage AI and Big Data to describe inner/intra daily trader's financial behaviour and further optimise and personalise the long temporal series of finance trading and long-term investing. Besides introduction of method and theory, Dr.Liu will bring up successful products and solutions, such as FDTScore for top trader selection, FDT robot advisor cloud for wealth management, intelligent resource allocation for hedge fund trading optimisation, intelligent market prediction for day-trading…

Abstract: This presentation introduces WeBank's positioning on FinTech - an enabler of inclusive finance. By leveraging advances in technologies such as AI, Blockchain, Cloud computing and Big Data, users’ experience can be improved while reducing cost, thus bringing various financial services to a wider audience.

Abstract: Blockchain is an emerging technology with the potential to change the way businesses, industries, and public organizations conduct and verify transactions, thereby streamlining business processes, saving cost, and reducing the potential for fraud. Given such benefits, in our rapidly evolving digital economy, it won’t be long before blockchain technology is a key foundation for distributed enterprise and consumer applications. In this talk, Dr.Yan will introduce Microsoft’s newly announced Blockchain Framework - Coco, which is an open-source system that enables high-scale, confidential blockchain networks that meet all key enterprise requirements—providing a means to accelerate production enterprise adoption of blockchain technology. Besides Coco, some real Blockchain scenarios, Blockchain ecosystems and BaaS are also included in the talk.

Abstract: Financial Technologies are driving an unprecedented experience in many applications and the fundamental transformation in the industry. Dr.Lei will discuss the major challenges and opportunities in this ever-changing world of FinTech - the intersection of finance and technology.

Abstract: Machine learning tools promise to help solve data curation problems. While the principles are well understood, the engineering details in configuring and deploying ML techniques are the biggest hurdle. In this talk Prof.Ihab discuss why leveraging data semantics and domain-specific knowledge is key in delivering the optimizations necessary for truly scalable ML curation solutions. The talk focuses on two main problems: (1) entity consolidation, which is arguably the most difficult data curation challenge because it is notoriously complex and hard to scale; and (2) using probabilistic inference to suggest data repair for identified errors and anomalies using our new system called HoloCLean. Both problems have been challenging researchers and practitioners for decades due to the fundamentally combinatorial explosion in the space of solutions and the lack of ground truth. There’s a large body of work on this problem by both academia and industry. Techniques have included human curation, rules-based systems, and automatic discovery of clusters using predefined thresholds on record similarity Unfortunately, none of these techniques alone has been able to provide sufficient accuracy and scalability. The talk aims at providing deeper insight into the entity consolidation and data repair problems and discusses how machine learning, human expertise, and problem semantics collectively can deliver a scalable, high-accuracy solution.

Abstract: AI needs to find the “right” business setting to be truly beneficial. In FINTECH area, AI can naturally become an enabling technology. In this talk, Prof.Yang will give an overview of AI + FINTECH and highlight some examples of successful applications.