This programme aims to impart inter-disciplinary knowledge of FinTech and legal regulations to students who are interested in the latest applications of FinTech and related legal issues. It examines contemporary elements and issues of FinTech and applies computational tools to finance and investment through practical workshops in the computer laboratory. The programme illustrates the applications of AI, RegTech, blockchain and robo advisory as well as explains the regulatory framework and statutory compliance.

Programme Intended Learning Outcomes:

On completion of the programme, students should be able to:
1. examine legal and regulatory frameworks in relation to FinTech; 
2. discuss the applications of FinTech and RegTech in finance and investment and examine their related legal regulations and statutory compliance issues;
3. use computational tools to illustrate the applications of FinTech and apply AI algorithms for finance and investment;
4. examine RegTech and robo advisory for investment and financial applications; 
5. analyse financial data and perform financial analytics and portfolio management.

Programme Structure

• Module 1: FinTech: Law and Regulation (30 hours)
• Module 2: AI and Financial Computing (42 hours)
• Module 3: Machine Learning for Financial Analytics (33 hours)
• Module 4: Regulatory Framework of Blockchain and Digital Currency (30 hours)
• Module 5: RegTech Applications in Finance (33 hours)
• Module 6: Robo Advisory and Portfolio Management (42 hours)

Award:

Students who complete all six modules with over 70% attendance and pass all individual assignments and group presentations will be awarded the Postgraduate Diploma in FinTech and Legal Regulations within the HKU system through HKU SPACE.

Application Code	2270-FN078A	Apply Online Now
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Module 1: FinTech: Law and Regulation

• Introduction to the regulatory framework and compliance issues for banking and securities investments
• The evolving relationship between FinTechs, regulators, and traditional financial institutions
• Banking regulations and policies in Hong Kong and overseas
• Blockchain, data privacy and security
• Regulatory and legal issues around FinTech
• Legal compliance of Anti-Money Laundering (AML) and Counter-Terrorist Financing (CFT)
• Legal issues and policies for wealth management under WealthTech and InsurTech
• RegTech, SupTech, LegalTech and the future of compliance

Assessment: Written assignment + One group project and group report

 

Module 2: AI and Financial Computing

• Principles of finance
• Overview of AI in finance
• Introduction to Python programming
• Mathematical and computational methods for finance

Assessment: Two assignments  + One group project and group report

 

Module 3: Machine Learning for Financial Analytics

• Introduction to machine learning and financial analytics
• Machine learning and algorithms
• Financial modelling and financial analytics

Assessment: Two assignments  + One group project and group report

 

Module 4: Regulatory Framework of Blockchain and Digital Currency

• Introduction to blockchains and digital currencies
• Introduction to smart contracts and governance design
• Regulation of finance and securities markets in the age of blockchain
• Cryptoassets, Initial Coin Offerings (ICOs) and their regulatory framework
• Digital identity and privacy
• The intersection of blockchain technologies with existing legal frameworks
• Legal services use-cases for blockchains and digital currencies

Assessment: Written assignment + One group project  and group report 

 

Module 5: RegTech Applications in Finance

• Introduction to Regulatory Technology (RegTech)
• RegTech for Financial Institutions in Hong Kong​
• Innovative technology around RegTech
• Capabilities and applications of RegTech in banking and finance

Assessment: Two assignments  + One group project and group report

 

Module 6: Robo Advisory and Portfolio Management

• Essentials of Robo Advisory and Automated Investment
• Introduction to portfolio construction
• Asset allocation and portfolio management

Assessment: Two assignments  + One group project and group report

 

Teachers
 

Mr Knut Fournier
Mr. Fournier is a US-qualified lawyer and experienced law professional. He worked in competition law compliance in London, before moving in-house. He specialises in the media and technology sectors and worked on complex e-commerce, consumer protection, and payment regulation matters. He is now the APAC Head of Legal for StubHub, the ticketing company. Knut published extensively on competition law and technology. He taught law at the City University of Hong Kong, and Shue Yan University.

Mr Clive Yip
Mr. Yip is a practitioner in Data Analytics.  He has 10 years of experience in both Big 4 consulting firms and multinational companies.  He is currently working as a Senior Data Analytics Consultant in a leading insurance company, using Python, SQL, and other Big Data technologies to analyse and monitor any non-compliance or fraudulent activities.  He has a Master’s degree in Information Technology from HKUST and a Bachelor’s degree from the University of Southern California.  Before entering the data analytics field, he worked as a financial auditor at Ernst and Young and is a Certified Public Accountant (CPA) in Hong Kong and Canada.

Mr Hong Lin
Mr. Lin has fruitful experience in Fintech development and digital transformation across retail and institutional businesses in Citigroup. Over the past three years, Mr. Lin has acted as an innovator by promoting big data analysis and managing a series of automation projects, covering the full process from streamlining to solution delivery with Automation Anywhere, Python, and VBA. His primary task has recently been to digitalize the business risk management for the bank’s prime brokerage business with data and automation technologies.
Mr. Lin started his career journey as a business intelligence engineer focusing on Fintech solution development and sales opportunities discovery thru data analysis. In 2017, he engaged in an AI Financial Advisory development by backward engineering trading strategies and analyzing financial news with Natural Language Processing techniques (NLP) in Ping An Securities. In 2018, Mr. Lin led a market research project to optimize product lines by analyzing more than 100,000 lines of customer reviews on the Internet with web-scraping and NLP. 
Mr. Lin graduated from the University of California, Davis with a Bachelor of Science degree in Managerial Economics Development under Trade and Development of Agricultural Commodities, and from the Hong Kong University of Science and Technology with a Master of Science degree in Business Analytics.

Mr Ken Liu
Mr. Liu is the co-founder and CTO of Datatact Ltd, a startup focused on AI, Machine Learning, and Big Data analytics. He is a hands-on expert in his specialized area for over 10 years.  Prior to Datatact, Ken worked at Citi, HSBC, Goldman Sachs, Deutsche Bank, and Credit Suisse as an Algo-Trading developer. Ken earned a Master's in Computer Science from USC and a Bachelor's in Computer Science from the University of Warwick.

Mr Joshua Chu 
Mr. Chu is the Chief Risk Officer at Coinllectibles™, the first publicly traded blockchain Fusion DOTs™ technology company in the US OTC Markets. He is also a Litigation Solicitor qualified to practice in Hong Kong. Before becoming a lawyer, Mr. Chu worked in the healthcare industry serving as the IT department head at a private hospital and overseeing their procurement operations.
Aside from his roles as a Chief Risk Officer and Lawyer, Mr. Chu is currently also a Senior Consultant with Prosynergy, a regulatory consulting firm that had been founded by ex-SFC Regulators as well as a management consultant for the Korean Blockchain Centre.

Mr Ken Tsoi
Ken has over 10 years of full-time working experience across start-ups, data software companies, retail banking, insurance companies, listed co., and large MNC FI firms in areas of AI, business intelligence, big data and machine learning. He is currently working in a Hang Seng Index listed company as a Senior Data Scientist in charging of data projects which are related on Predictive Analytics, Business Automation and Neural Network. He has been teaching and coaching on different institutes and schools over the decade and is a professional on communicating abstract data concept and theory to layman and student in an efficient and effective way. He holds Bachelor (Hon) of Statistics and Operation Research in HKBU and Master of Statistics and Risk Management in HKU. He is a certified FRM (Financial Risk Management) Professional, Certified Statistical Business Analyst; Certified Predictive Modeler: Enterprise Miner; Certified Advanced Programmer; Certified Base Programmer; and Certified System Platform Administrator, all 5 Credentials were approved by SAS Institute.

Dr Simon Yiu
Simon, IT Department Head of a financial institution in Hong Kong, has handled many FinTech initiatives and projects, such as Algo trading, finance big data analytics, Robo-advisors and so on. Before that, he also worked for AI, and Machine learning startup as co-founder and CTO which located at a Hong Kong Science Park and participated at the University organized Entrepreneurship Center in 2010, focusing on AI, Machine Learning, Big Data analytics and Natural language processing. Furthermore, he has hands-on programming experiences in FinTech areas for over 10 years. Simon earned a Doctoral Degree in Business Administration from the City University of Hong Kong and a Master Degree in Data Science and Business Statistics from The Chinese University of Hong Kong.

Class Schedule (Jan 2024 intake)

Class Schedule (Mar 2024 intake)

Class Schedule (May 2024 intake)

Class Schedule ()

Class Schedule (Nov 2024 intake)

Class Schedule (Feb2025 intake)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Application Fee

HK$150 (Non-refundable)

Course Fee

• Module fee: $11,000 (course fees are subject to change without prior notice)
  2 installment-:1st- three modules: $33,000 and 2nd- three modules: $33,000

Applicants shall hold a bachelor’s degree in quantitative or computational areas (e.g., economics, finance, mathematics, statistics, science, computer science, IT, engineering) awarded by a recognized institution or equivalent.

If the degree or equivalent qualification is from an institution where the language of teaching and assessment is not English, applicants shall provide evidence of English proficiency, such as: 
i. an overall band of 6.0 or above with no subtests lower than 5.5 in the IELTS; or
ii. a score of 550 or above in the paper-based TOEFL, or a score of 213 or above in the computer-based TOEFL, or a score of 80 or above in the internet-based TOEFL; or 
iii. HKALE Use of English at Grade E or above; or
iv. HKDSE Examination English Language at Level 3 or above; or
v. equivalent qualifications. 

Applicants who hold the Advanced Diploma for Legal Executives (Graduate Level) awarded within the HKU system through HKU SPACE would be eligible for entry.
Applicants without undergraduate qualifications, but have substantial work experience will be considered on individual merit.

Applicants who do not have a background in quantitative or computational areas are required to take the Certificate for Module (Quantitative Methods in Finance) as the bridging course. They must complete and pass the module before the commencement of the programme.

• The CEF Institution Code of HKU SPACE is 100

CEF Courses
AI and Financial Computing (Module from Postgraduate Diploma in FinTech and Legal Regulations)
COURSE CODE 33Z138909	FEES $11,000	ENQUIRY 2867-8331
Machine Learning for Financial Analytics (Module from Postgraduate Diploma in FinTech and Legal Regulations)
COURSE CODE 33Z138917	FEES $11,000	ENQUIRY 2867-8331
RegTech Applications in Finance (Module from Postgraduate Diploma in FinTech and Legal Regulations)
COURSE CODE 33Z138925	FEES $11,000	ENQUIRY 2867-8331
Robo Advisory and Portfolio Management (Module from Postgraduate Diploma in FinTech and Legal Regulations)
COURSE CODE 33Z138933	FEES $11,000	ENQUIRY 2867-8331
FinTech: Law and Regulations (Module from Postgraduate Diploma in FinTech and Legal Regulations)
COURSE CODE 33Z141306	FEES HK$11,000	ENQUIRY 2520-4617
Regulatory Framework of Blockchain and Digital Currency (Module from Postgraduate Diploma in FinTech and Legal Regulations)
COURSE CODE 33Z141314	FEES HK$11,000	ENQUIRY 2520-4617

	Continuing Education Fund Reimbursable Course (selected modules only) Some modules of this course have been included in the list of reimbursable courses under the Continuing Education Fund.
	Postgraduate Diploma in FinTech and Legal Regulations This course is recognised under the Qualifications Framework (QF Level [6])

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Hong Kong Digital Asset Society (HKDAS) is led by a volunteer group of members who care about the future of financial technology in Hong Kong, Greater China and Asia. We are not-for-profit and have an independent structure based on our three pillars of values:  trust, transparency, and governance. We aim to develop and promote the four areas of the Digital Asset industry in Hong Kong.

Education - Provide lectures, mentoring services, workshops and necessary training to educate the public and students on the latest development in digital assets and blockchain technology.

Incubation - Support local entrepreneurs who try to build start-ups in the digital asset space. We help incubate and accelerate their growth by providing necessary training, support and resources.

Opportunity - Provide opportunities like gap year placement, internship and graduate trainee programme to grow and equip young talents and leaders and help them be ready for this evolving and innovative environment.

Integration - Encourage integrations and collaborations with regulators and industrial organizations locally and overseas. Increase investors’ confidence by promoting agreement on the industrial standards for products, practices or operations in the field.