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Accounting & Finance FinTech and Financial Analytics

Certificate for Module (AI-Driven Autonomous Finance)
證書(單元 : 運用人工智能推動自主金融)

Course Code
FN176A
Application Code
2435-FN176A

Credit
6
Study mode
Part-time
Start Date
18 Jul 2026 (Sat)
Next intake(s)
Oct 2026
Duration
30 hours
Language
English
Course Fee
Course Fee: HK$10,800 per programme (* course fees are subject to change without prior notice)
Deadline on 08 Jul 2026 (Wed)
Enquiries
2867 8331 / 2867 8424
2861 0278
Apply Now

Accept new applications for Jul 26 intake! There will be practical classes in the computer laboratory.

Highlights

The programme aims to provide students with strategic and technical perspectives in the transition from traditional digital banking to artificial intelligence-driven autonomous finance. Students will explore the convergence of Web 4.0 autonomous agents, programmable money, and tokenised real-world assets (RWAs) to understand how machine-to-machine commerce is reshaping global markets. By examining multi-agent systems, privacy-preserving technologies like zero-knowledge proofs, and regulatory-as-code frameworks, the programme covers the architecture and management of invisible financial ecosystems. The programme also equips students with the multidisciplinary expertise required to design, govern, and scale autonomous financial systems that are secure, compliant, and hyper-personalised within a rapidly evolving, modular, decentralised finance (DeFi) landscape.

Programme Details

On completion of the programme, students should be able to 
1.    critically evaluate the technological elements of artificial intelligence (AI) and autonomous finance, and explain the evolution of financial systems, agentic AI and smart infrastructure;
2.    assess regulatory and governance issues, and investigate the interaction of autonomous components among programmable money, modular decentralised finance, and privacy-preserving infrastructure;
3.    analyse the implications of tokenised assets, autonomous markets and related operations, and design collaborative AI frameworks by applying computational tools and software to implement autonomous finance; and
4.    discuss multi-agent systems, smart contracts, hyper-personalisation, credit assessment, explainable AI, supervisory technology, and the future workforce in finance.
 

Application Code 2435-FN176A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 2:00pm - 5:45pm
Duration
  • 30 hours per programme
Venue
  • Hong Kong Island Learning Centre
  • Kowloon West Campus
  • Kowloon East Campus

Modules

Course Content :

(1) The emergence of autonomous finance

  • Overview of financial technology (FinTech) ecosystem and developments in autonomous finance
  • The web continuum: from Web 2.0 to Web 4.0
  • Human-machine interaction (HMI) in finance
  • Emerging technologies in autonomous finance
    • Machine readability of financial data
    • Artificial intelligence (AI) agents and large language models (LLMs)
    • Agentic commerce
  • AI-driven automated financial reporting

(2) Autonomous workforce and agentic AI in financial systems

  • Comparison between agentic AI and predictive AI
  • Financial AI agent archetypes
  • Introduction to computational tools and software for autonomous finance
  • Boundaries of autonomy and governance models
  • Multi-agent systems and LLMs in finance
    • Agentic workflows in corporate banking
    • Multi-agent systems for a syndicated loan process

(3) Programmable money and smart infrastructure

  • Fundamentals of programmable money
  • Account abstraction (ERC-4337 and EIP-7702)
  • Central bank digital currencies (CBDCs)
  • Smarter settlement
  • Atomic transactions
  • Atomic settlement layers
  • Conditional payments powered by smart contract in trade finance

(4) Tokenised assets and real-world assets (RWAs)

  • Overview of tokenisation and on-chain assets
  • RWAs lifecycle on-chain and new financial services
  • Fractionalisation and new asset classes
  • AI-driven market making and valuation

(5) Autonomous markets, modular decentralised finance (DeFi) and intelligent liquidity

  • Modular DeFi stacks
  • Automated market makers (AMMs) and intelligent liquidity protocols
  • Institutional DeFi and compliance
  • Interoperability imperative and cross-chain communication protocols

(6) Embedded and invisible autonomous finance

  • Basic terminologies of embedded finance
  • Capabilities of autonomous finance
  • Hyper-personalisation in banking and finance

(7) Trust, identity and privacy-preserving infrastructure

  • Zero-knowledge proofs (ZKPs)
  • Self-sovereign identity (SSI) and verifiable credentials
  • Trust matrix: human-machine and machine-machine trust models
  • Advanced privacy-enhancing techniques
  • ZK-based credit assessment

(8) Governance, explainability and regulatory automation

  • Explainable AI (XAI) for finance
  • Regulation-as-code and regulatory automation
  • Supervisory technology (SupTech)
  • Emergency controls and kill switches
  • Regulatory, risk and governance issues in automation

(9) The autonomous operating model and future workforce

  • Financial digital twins
  • Digital twin technology in banking and finance
  • Future operations in finance

Assessment method: In-class Exercise + Group Project Presentation

 

Award

Upon successful completion of the programme, students who have passed the assessments with attendance no less than 70% will be awarded within the HKU system through HKU SPACE a "Certificate for Module (Artificial Intelligence-Driven Autonomous Finance)".

Class Details

Timetable

Lecture

Date

Time

1

18 Jul 26 (Sat)

14:00 – 17:45

2

25 Jul 26 (Sat)

14:00 – 17:45

3

1 Aug 26 (Sat)

14:00 – 17:45

4

8 Aug 26 (Sat)

14:00 – 17:45

5

15 Aug 26 (Sat)

14:00 – 17:45

6

22 Aug 26 (Sat)

14:00 – 17:45

7

29 Aug 26 (Sat)

14:00 – 17:45

8

5 Sep 26 (Sat)

14:00 – 17:45

Teacher Information

Ms Irene Lam

Background

Ms Irene Lam has over 15 years of experience in audit, risk management, compliance, and Anti-Money Laundering/Counter-Financing of Terrorism (AML/CFT) within the financial services industry. She has worked at several Globally Systemically Important Banks (G-SIBs), including Standard Chartered Bank, HSBC (via Hang Seng Bank), and Mizuho Bank. Her expertise lies in managing enterprise, operational, cybersecurity, and technology risks. She has experience as a 3rd-line auditor, 2nd-line risk steward, and 1st-line risk professional, and has managed artificial intelligence proof-of-concept projects. Her experience also includes conducting threat scenario-led risk analyses, institutional risk landscape assessments, thematic reviews, and audits of financial products and electronic platforms. Additionally, she oversaw regulatory matters as a designated manager under the Payment Systems and Stored Value Facilities Ordinance  (Cap. 584).

She holds a Master of Information Systems Studies from the Australian National University, a Bachelor of Commerce from the University of Melbourne, and a Diploma in China (Commercial) Law from Shenzhen University. Her certifications include Certified Information Systems Auditor (CISA), Certified Ethical Hacker (CEH), Certified Internal Auditor (CIA), Certified Public Accountant (CPA), Certified Anti-Money Laundering Specialist (CAMS), and Certified Big Data Professional (CBDP).

Within her areas of expertise, she held the roles of Senior Vice President at a Hong Kong Monetary Authority Stored Value Facilities license holder and Associate Director at Standard Chartered Bank (Hong Kong) Limited.

Fee

Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee: HK$10,800 per programme (* course fees are subject to change without prior notice)

Entry Requirements

Applicants should hold an Advanced Diploma, Higher Diploma or Associate Degree awarded by a recognised institution where the language of teaching and assessment is English. Those with a background in business, accounting, finance, economics, mathematics, statistics, science, engineering, IT or computer science would have an advantage.

Applicants with other equivalent qualifications will be considered on individual merit.

**Please upload copy of HKID and proof of degree while applying online

Apply

Online Application Apply Now

Application Form Download Application Form

Enrolment Method
Payment Method
1. Cash, EPS, WeChat Pay Or Alipay

Course fees can be paid by cash, EPS, WeChat Pay or Alipay at any HKU SPACE Enrolment Centres.

2. Cheque Or Bank draft

Course fees can also be paid by crossed cheque or bank draft made payable to “HKU SPACE”. Please specify the programme title(s) for application and applicant’s name. You may either:

  • bring the completed form(s), together with the appropriate course or application fees in the form of a cheque, and any required supporting documents to any of the HKU SPACE enrolment centres;
  • or mail the above documents to any of the HKU SPACE Enrolment Centres, specifying “Course Application” on the envelope. HKU SPACE will not be responsible for any loss of personal information and payment sent by mail.
3. VISA/Mastercard

Applicants may also pay the course fee by VISA or Mastercard, including the “HKU SPACE Mastercard”, at any HKU SPACE enrolment centres. Holders of the HKU SPACE Mastercard can enjoy a 10-month interest-free instalment period for courses with a tuition fee worth a minimum of HK$2,000; however, the course applicant must also be the cardholder himself/herself. For enquiries, please contact our staff at any enrolment centres.

4. Online Payment

Online application / enrolment is offered for most open admission courses (enrolled on first come, first served basis) and selected award-bearing programmes. Application fees and course fees of these programmes/courses can be settled by using "PPS by Internet" (not available via mobile phones), VISA or Mastercard. In addition to the aforesaid online payment channels, new and continuing students of award-bearing programmes with available online service, they may also pay their course fees by Online WeChat Pay, Online Alipay or Faster Payment System (FPS). Please refer to Enrolment Methods - Online Enrolment  for details.

Notes

  • If the programme/course is starting within five working days, application by post is not recommended to avoid any delays. Applicants are advised to enrol in person at HKU SPACE Enrolment Centres and avoid making cheque payment under this circumstance.

  • Fees paid are not refundable except under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment), subject to the School’s discretion. In exceptional cases where a refund is approved, fees paid by cash, EPS, WeChat Pay, Alipay, cheque, FPS or PPS by Internet will be reimbursed by a cheque, and fees paid by credit card will be reimbursed to the credit card account used for payment. 

  • In addition to the published fees, there may be additional costs associated with individual programmes. Please refer to the relevant course brochures or direct any enquiries to the relevant programme team for details.
  • Fees and places on courses cannot be transferrable from one applicant to another. Once accepted onto a course, the student may not change to another course without approval from HKU SPACE. A processing fee of HK$120 will be levied on each approved transfer.
  • HKU SPACE will not be responsible for any loss of payment, receipt, or personal information sent by mail.
  • For payment certification, please submit a completed form, a sufficiently stamped and self-addressed envelope, and a crossed cheque for HK$30 per copy made payable to “HKU SPACE” to any of our enrolment centres.
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