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BusinessFinance and Investment

Executive Certificate in Big Data, Governance and Compliance

New Course
Course Code
Application Code
Study mode
Start Date
To be advised
Next intake(s)
March 2018
3 months
Course Fee
HK$6000 per programme
Apply Now
Deadline on 22 Nov 2017 (Wed)
2520 4612
2858 4750
***Nov Intake Confirm Launch***
2 tutors with different expertise in corporate governance, cybersecurity, banking compliance

Executive Certificate in Big Data, Governance and Compliance aims to provide students with an overview in Big Data potentials, fraud detection and prevention for corporates, banking and financial services.


The programme contents cover challenges and limitations in using Big Data in business. Key concepts include Big Data governance and compliance regulatory requirement, best practices in data protection and risk management.  Case studies will be used to explain the importance of fraud detection and prevention in reducing company losses. Case studies emphasis will be in banking and financial services sector. 

分業監管礙金融科技   by appledaily

Data governance framework: What is it…. by SAS

BIG DATA ANALYSIS AND ITS NEED FOR EFFECTIVE E-GOVERNANCE   International Journal of Innovations & Advancement in Computer Science 

Tips to reducing big data compliance risks   by TechRepublic

On completion of the programme, students should be able to:
1.     examine the Big Data handling process with ethical issues of Big Data collection and privacy protection within the financial services;
2.     discuss the Big Data governance as a corporate governance imperative;
3.     discuss the Big Data challenges and opportunities in banking and financial services;
4.     evaluate the risk and challenges in real life case studies of handling Big Data fraud detection and prevention;
5.     leverage current technology and Big Data to enhance governance and compliance;
6.     develop a privacy framework to protect privacy information from Big Data.

Application Code 1555-EP106A -

Days / Time
  • Thursday, 7:00pm - 10:00pm
  • 30 hours per module
  • 10 meeting(s)
  • 3 hours per meeting
Venue Tutor
  • Mr. Sokhiya has been a Manager in the Compliance Technology Division for a Japanese investment bank for the past 10 years. He is responsible for planning & tracking technology projects, managing compliance regulatory reporting & trade surveillance systems. He also worked as a Business analyst at Goldman Sachs from 2003-2007. His key areas of academic interests include latest trends in technology - big data, artificial intelligence and cloud technology, and organizational behaviour. Mr. Sokhiya earned an MBA from HKUST and a BEng from Vikram University in India.
  • Mr. Ng had been senior executive of Digital MNC, including the first online Agency in the States. Launched the first broadband e-commerce, 4G LTE and O2O Apps in Asia, the first mobile eShop, and also launched other brands included Apple iphone and other luxury brands. Dr. Ng engaged as guest lecturer and consultant for various domains, including local governments, NGO, corporates and startups in the region over 12 years.

Course Content: 

1.     What is Big Data?

2.     Big Data processing chain

-     Data, database, data warehouse, data mining, data visualization

3.     Defining Big Data – volume; velocity; variety; variability and veracity

4.     Big Data landscape

5.     Business and Technology implications of Big Data

6.     Management and Storage of Big Data – cloud storage

7.     Business Challenges and Big Data Opportunities in Financial Services and Banking:

-     Key business challenges

-     How can the financial services industry use Big Data?

A.     Asset Management Banking

B.     Banking

i)     Potential of Bank Customer Data:

- Customer Analytics: Customer segmentation for banking needs

- Personalized financial products offering

ii)     How can Banks realize greater value from customer data?

iii)     How can Banks scale-up to next level of customer data analytics?

iv)     How Big Data transforms Banking and Financial Services?

v)     Limitations for Banks to exploit Big Data

C.     Capital Markets

D.     Insurance

-     Enterprise modelling platform

-     Risk and capital management

-     Wealth management

-     Improving customer intimacy

-     Improving fraud detection

8.     Fraud detection and security

-     Fraud Detection Techniques with Predictive Analytics

-     Best practices for implementing Big Data for fraud prevention

-     How Big Data analytics enhances monitoring performance and enables quicker decisions in detecting suspicious behavior, uncovering threats and vulnerabilities, preventing security incidents, and backing up forensic analyses

-     Risk Prediction

-     Corporate Fraud detection and prevention

Cases: Preventing Health Care Fraud with Big Data and Analytics/ Insurance claims; Fraud monitoring and fraud risk management case: Big Data based fraud risk management at Alibaba

9.     Data Protection in the era of Big Data and the responsibility of information governance and compliance from a privacy prospective:

-     Potential challenges in the staggered data

-     Volume and sensitivity of data sets

-     Maximize potential of Big Data and protects privacy of consumers

-     Ambiguous data collection

-     Unauthorized sharing and unexpected uses of data

-     Heightened security risks

-     Potential for discrimination

-     Privacy framework with appropriate approach to notice and consent

-     Ethical and fair usage of Big Data to achieve value based innovation

-     Compliance and regulatory reporting

Assessment method: class participation + assignment

The Executive Certificate will be conferred to candidates who have attained PASS grade and achieved at least 70% attendance of the programme.

November intake:




Lecture  1

24 Nov 2017 (Fri)


Lecture  2

27 Nov 2017 (Mon)

Lecture  3

30 Nov 2017 (Thu)

Lecture  4

7 Dec 2017 (Thu)

Lecture  5

21 Dec 2017 (Thu)

Lecture  6

4 Jan 2018 (Thu)

Lecture  7

11 Jan 2018 (Thu)

Lecture  8

18 Jan 2018 (Thu)

Lecture  9

25 Jan 2018 (Thu)

Lecture  10

1 Feb 2018 (Thu)

Applicants shall hold:
a)    a bachelor’s degree awarded by a recognized University or equivalent; or
b)   an Associate Degree/ a Higher Diploma or equivalent, and have at least 2 years of relevant working experience.

Applicants with other qualification and substantial senior level work experience will be considered on individual merit.

Application Fee

HK$150 (student only needs to pay one time application fee for all EC in Big Data Series)

Course Fee
  • Course Fee : HK$6000 per programme

Application Form Download Application Form

Enrolment Method

We provide online application and payment service for students to make enrolment via the Internet. Enrolment will be confirmed once students have made the payment online by using either PPS or credit card.

For first-come, first-served courses:
  1. Complete the online application form
    Click the "Apply Now" button on the top right hand corner of the course webpage to make online application. Follow the instructions to fill-in the online application form.
  2. Make Online Payment
    Pay the course fees by either using

    PPS via Internet - You will need a PPS account and a PPS Internet password. For information on how to open a PPS account and how to set up a PPS Internet password, please visit

    Credit Card Online Payment - Course fees can be paid by VISA or MasterCard via a secure online payment gateway for all first-come, first-served courses.

For award-bearing programmes:

Selected award-bearing programmes also provide online enrolment and payment service for its students.

If your programme accepts online enrolment and payment, a re-enrolment icon will be shown on the course webpage. Click the icon and follow the instructions to perform online enrolment and payment. You will receive relevant information from the programme team nearer the time of enrolment.

You may click here directly to access the online enrolment and payment service.

Please note the followings:

  1. Admission is on a first-come, first-served basis. Enrolment will be confirmed once you have made the payment online. You will receive a payment confirmation after payment has been made successfully. You are advised to keep your payment confirmation for future enquiries.
  2. Fees paid are not refundable except as statutorily provided or under very exceptional circumstances.
  3. To make an application online, you will need a computer with connection to the Internet and a web browser with JavaScript enabled. Internet Explorer 5.01 or above is recommended as the web browser.


The School provides a platform for online services for a selected range of products it offers. While every effort is made to ensure timeliness and accuracy of information contained in this website, such information and materials are provided "as is" without express or implied warranty of any kind. In particular, no warranty or assurance regarding non-infringement, security, accuracy, fitness for a purpose or freedom from computer viruses is given in connection with such information and materials.

The School (and its respective employees and subsidiaries) is not liable for any loss or damage in connection with any online payments made by you by reason of (i) any failure, delay, interruption, suspension or restriction of the transmission of any information or message from any payment gateways of the relevant banks and/or third party merchants for processing credit/debit/smart card or other payment facilitation mechanism; (ii) any negligence, mistake, error in or omission from any information or message transmitted from the said payment gateways; (iii) any breakdown, malfunction or failure of those gateways in effecting online payment service or (iv) anything arisen out of or in connection with the said payment gateways, including but not limited to unauthorised access to or alternation of the transmission of data or any unlawful act not permitted by the law.

Payment Method
1. Cash or EPS

Course fees can be paid by cash or EPS at any HKU SPACE enrolment counters.

2. Cheque or bank draft

Course fees can also be paid by crossed cheque or bank draft made payable to “HKU SPACE”. Please specify theprogramme 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 payment sent by mail.
3. VISA/MasterCard

Applicants may also pay the course fee by VISA or MasterCard, including the “HKU SPACE MasterCard”, at anyHKU SPACE enrolment centres. Holders of the HKU SPACE MasterCard can enjoy a 10-month interest-freeinstalment 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

The course fees of all open admission courses (course enrolled on first come, first served basis) and selected award-bearing programmes can be settled by using PPS via the Internet. Applicants may also pay the relevant course fees by VISA or MasterCard online. Please refer to the Online Services page on the School website.


  1. For general and short courses, applicants may be required to pay the course fee in cash or by EPS, Visa or MasterCard if the course is to start shortly.

  2. 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, cheque or PPS (for online payment only) will normally be reimbursed by a cheque, and fees paid by credit card will normally be reimbursed to the payment cardholder’s credit card account.

  3. 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.
  4. Fees and places on courses cannot be transferred 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 approved transfers.
  5. Receipts will be issued for fees paid but HKU SPACE will not be responsible for any loss of receipt sent by mail.
  6. For additional copies of receipts, please send a stamped, self-addressed envelope with a completed form and a crossed cheque for HK$30 per copy made payable to ‘HKU SPACE’. Such copies will only normally be issued at the end of a course.