HKU-Cyberport Leading FinTech Ventures
Programme
HKU-Cyberport Leading FinTech Ventures
Programme Length
10 Days (10 modules, 1 day each)
Programme Fee
HK$60,000
2/3 course fee reimbursement upon successful RTTP application. Click here for more information.
Medium of Instruction
English
Delivery Approach
Face-to-face
ABOUT THE PROGRAMME
Financial Technology (Fintech) represents a combination of financial services with Information Technology (IT). From making mobile payments to handling complex financial data at work, FinTech has (and will continue to) defined the direction, shape, and pace of change across many industry sectors.
To meet the current and future demands, the HKU-Cyberport Leading FinTech Ventures programme aims to groom leaders and talents for the future FinTech in Hong Kong and the Greater Bay Area.
Driving deep on both financial and technological considerations, the programme is designed to equip participants with in-depth knowledge and skills at the intersection of technology, financial services and entrepreneurship. The programme is ideal for FinTech enthusiasts who are looking to launch a FinTech startup or implement innovation projects within an incumbent. The programme is unique by drawing renowned Faculty members from HKU Business School, Department of Computer Science, Faculty of Law as well as the incubation programmes for Fintech Ventures offered by Hong Kong Cyberport Management Company Limited.
WHO SHOULD ATTEND
- Aspiring FinTech entrepreneurs and technical leaders of FinTech startups seeking to gain solid knowledge foundation of the Fintech tools that add value to the ventures,
- Mid- to senior level managers on the technical side of things who are (or about to be) involved in Fintech projects and initiatives in their respective organisations in the banking and financial services industry,
- Professionals, who are interested in gaining a deeper understanding of FinTech trends, ecosystems, tools and methods of executing financial technology innovations.
PROGRAMME STRUCTURE
Module 1:
Clustered and Cloud Computing
- Various issues in the design and implementation of cloud systems
- Cloud delivery models (SaaS, PaaS, and IaaS) with motivating examples from Google, Amazon, and Microsoft; virtualisation techniques implemented in Xen, KVM, VMWare, and Docker
- Distributed file systems, such as Hadoop file system; MapReduce and Spark programming models for large-scale data analysis
- Networking techniques in cluster and hyper-scale data centres
Module 2:
Cyber and Information Security
- Introduces the principles, mechanisms and implementation of cyber security and information protection
- Introduction to cryptography; symmetric key cryptography and public key cryptography & PKI (Public-key infrastructure)
- Introduction to hashing and integrity
- Authentication techniques: authentication protocols, access controls and security policy
- Network and Internet security: Firewall, IDS, application, wireless and web security
- Incidence response, penetration test, and cyber threat assessment
Module 3:
Alternative Data in Financial Asset Pricing and Investment
- Advances in Artificial Intelligence.
- Machine Learning practice in credit market.
- Advances of Machine Learning research in financial asset pricing.
- Machine Learning practice in quantative trading.
- What to do and what not to do with Machine Learning when applying to financial market.
Module 4:
Machine Learning and Artificial Intelligence in Finance
- Learn the alternative data landscape, types of data, sources of data collection, industry vendors
- Understand various use cases of big and alternative data in quantitative and traditional discretionary trading
- Discuss developing issues related to privacy, compliance and other legal considerations
Module 5:
Blockchain, Smart Contracts and DeFi
- Textual Analysis for Policy Interpretation
- Cryptocurrency, Trust, and Social Media
- Cross-border Digital Transfer
Module 6:
Entrepreneurial Finance and Innovation Strategy
- Investment Strategies of PE, VC, and CVC
- New Trends in M&A / IPO
- SPACs
- Value of Financial Innovations
Module 7:
Financial Innovations and FinTech Market Development
- Fintech Credit Market Development
- Financing the Fintech Credit
- Joint Lending and Business Models in FinTech Credit Market
- Credit Information Sharing and New Regulation
- Structured Finance and Credit Derivatives in FinTech Market
- Blockchain Applications in Supply Chain Finance
- Blockchain Applications in Trade and International Finance
Module 8:
Privacy Enhancing Technologies and Federated Learning
- An introduction to the concept of “privacy”
- Existing ordinance and regulations related to privacy in different countries / regions and how it affects the issues of data trading and sharing
- Introduction to privacy enhancing technologies
- Introduction to federated learning
- How to share / trade data or information of data while protecting the privacy and the trade secrets of the data using existing technologies
- The future trend of data sharing and trading in finance
Module 9:
Regulation, Data Privacy and Competition Law
- Introduction to key regulatory issues for FinTechs
- Financial regulation: Banking, securities, insurance
- Data regulation: Cybersecurity, privacy, outsourcing – Local, crossborder
- RegTech and SupTech
- Other regulatory concerns: Competition, telecoms and beyond
Module 10:
Behavioural Science and its Applications in FinTech
- Why personal behavioural traits matter: the value of understanding and applying behavioral knowledge in fintech
- Basic knowledge of behavioural science: the commonly faced behavioral patterns and the roles they play in finance
- How to capture personal behaviours in big data: what data is relevant and how to use the data to compute relevant features
- Incorporating behavioural features in fintech applications: application in the credit models, in investment product design, in “nudging” customer choices, etc.
LEARNING EXPERIENCE
The uniqueness of the programme is the blending of both the conceptual framework and practical knowledge together. There will be interactive discussion, case studies, industrial visits, exclusive dialogues with practitioners on fintech ventures and development.
Such developmental experience aims to provide you with the opportunity to prepare for commencement in the entrepreneurial journey in Fintech.
FACULTY PROFILES
Prof. Chen Lin
Associate Dean (Research and Knowledge Exchange)
Chair of Finance
Stelux Professor in Finance
Director, Centre for Financial Innovation and Development
DBA Programme Director
Academic & Professional Qualification
Ph.D., M.A., M.B.A., University of Florida
B.E., South China University of Technology
Prof. Douglas Arner
Kerry Holdings Professor in Law
RGC Senior Fellow in Digital Finance and Sustainable Development
Associate Dean (Taught Postgraduate & Development), Faculty of Law
Associate Director, HKU-Standard Chartered FinTech Academy
University of Hong Kong
Academic & Professional Qualification
Ph.D, University of London
LLM, Southern Methodist University
BA, Drury College
Prof. Yiu, Siu Ming
Associate Head (Teaching and Learning)
Professor
Academic & Professional Qualification
Ph.D., HK
MS, Temple University
BSc, CUHK
Dr. Luo Ye
Associate Professor
Academic & Professional Qualification
Ph.D., Massachusetts Institute of Technology
B.S., Massachusetts Institute of Technology
Dr. Mingzhu Tai
Assistant Professor
Academic & Professional Qualification
Ph.D. in Business Economics, Harvard University
Master and Bachelor degrees in Finance, Tsinghua University
Dr. Yang You
Assistant Professor
Academic & Professional Qualification
Ph.D., Harvard University
Bachelor in Economics and Mathematics, Tsinghua University
SCHEDULE AND VENUE
Dates
| M1 | Clustered and Cloud Computing |
| M2 | Cyber and Information Security |
| M3 | Alternative Data in Financial Asset Pricing and Investment |
| M4 | Machine Learning and Artificial Intelligence in Finance |
| M5 | Blockchain, Smart Contracts and DeFi |
| M6 | Entrepreneurial Finance and Innovation Strategy |
| M7 | Financial Innovations and FinTech Market Development |
| M8 | Privacy Enhancing Technologies and Federated Learning |
| M9 | Regulation, Data Privacy and Competition Law |
| M10 | Behavioural Science and its Applications in FinTech |
| M1 | Clustered and Cloud Computing | Date to be confirmed |
| M2 | Cyber and Information Security | Date to be confirmed |
| M3 | Alternative Data in Financial Asset Pricing and Investment | Date to be confirmed |
| M4 | Machine Learning and Artificial Intelligence in Finance | Date to be confirmed |
| M5 | Blockchain, Smart Contracts and DeFi | Date to be confirmed |
| M6 | Entrepreneurial Finance and Innovation Strategy | Date to be confirmed |
| M7 | Financial Innovations and FinTech Market Development | Date to be confirmed |
| M8 | Privacy Enhancing Technologies and Federated Learning | Date to be confirmed |
| M9 | Regulation, Data Privacy and Competition Law | Date to be confirmed |
| M10 | Behavioural Science and its Applications in FinTech | Date to be confirmed |
Venue
HKU Business School
Main Campus / Cyberport Campus / Town Centre (Admiralty Centre)
or
Cyberport Academy
100 Cyberport Road,
Hong Kong
FEES AND FUNDING
Full programme fee:
HK$60,000 per participant
This Programme has been included in the list of registered public courses under the under “Reindustrialisation and Technology Training Programme” (RTTP) which offers 2/3 course fee reimbursement upon successful application.
Discounts*
| Type | Discount | Eligibility |
| Early Bird | 10% | Registration has to be submitted before 30 November 2022. |
| Group | 15% | Minimum of three participants from the same organisation registering for the programme. |
| HKU Alumni and Staff | 20% | Please indicate your alumni status in your registration, and we will advise and confirm on your eligibility. |
*Only one type of discount can be applied per enrollment. The discount cannot be used in conjunction with other promotions, discounts or offers. In the event of a dispute, provision of the discount(s) is subject to the sole discretion and final decision of HKU Business School.
What is RTTP?
Reindustrialisation and Technology Training Programme (RTTP) is a funding programme under the HKSAR Government’s Technology Talent Scheme. It aims at subsidising local companies on a 2:1 matching basis to train their staff in advanced technologies, especially those related to Industry 4.0. The maximum annual funding is HK$500,000 for each eligible company. 50% of the approved training grant can be released to the companies upon request before course completion.
Approved Reindustrialisation and Technology Training Programme (RTTP) offers 2/3 course fee reimbursement upon successful applications. For details: https://rttp.vtc.edu.hk.
RTTP Training Grant Application
Companies should submit their RTTP training grant application for their employee(s) via https://rttp.vtc.edu.hk/rttp/login at least two weeks before course commencement. Alternatively, application form could be submitted by email to rttp@vtc.edu.hk along with supporting documents.
