(Offered by Department of Statistics)
|(852) 3943 7931
|Admission||Risk Management Science (JS4719)|
The Programme of Risk Management Science has been the leading pioneer in nurturing well-trained professionals in the risk management fields since its foundation in 2000. The Programme is suitable for students who have strong aspirations towards mathematical and scientific methodologies, and are interested to pursue a career in the financial industry and related areas.
The curriculum of Risk Management Science is designed to equip students with the knowledge and skills to understand risk management from both theoretical and application perspectives in insurance, finance and other related areas. Risk management is an interdisciplinary subject, so in addition to statistics, our students will receive a solid training in other foundation subjects including finance, economics, accounting, mathematics and computer science.
Risk Analytics Stream
The Risk Analytics Stream places special emphasis on statistical science and computer science, including but not limited to subjects such as statistical inference, actuarial science and financial mathematics. Upon graduation, students are well-equipped to become professional risk managers with a strong background in data science and data analytics. Job referral services on internships and graduate jobs and opportunities for further studies will be provided to students of the stream.
- JP Morgan
- Goldman Sachs
- Morgan Stanley
- BNP Paribas
- Standard Chartered
- Bank of East Asia
- Deloitte & Touche
- Ernst & Young
- HSBC Insurance (Asia)
- AIA Company Ltd
- Aon Hong Kong
- Hong Kong Monetary Authority
Operations Analyst, Goldman Sachs
The Programme of Risk Management Science was challenging but certainly rewarding to those who took the opportunity to develop themselves. Personally, the Programme provided me with analytical skills and the appropriate mindset to approach problems; I was not simply taught the solution but gained the ability to understand the scenario, break down the problem into pieces and then derive the solution. This approach is helpful in a general sense, providing more possibilities after graduation, either in advanced studies or in professional careers across all fields.