Trix ZHANG

BSc in Risk Management Science
Deloitte

I joined Deloitte HK Risk Advisory Cyber as an intern in the Architect & Engineering Team. During my internship, I assisted in various projects ranging from a technical review of a client’s network infrastructure via independent assessment to remediation of a client’s internal governance on information security risk management through policy design. While giving my recommendations based on the findings from my assessment, I genuinely felt that I was assisted by the risk management mindset I gained during my undergraduate education as an RMSC student.

Working in this division involved assessing clients’ cybersecurity risks, developing strategies to mitigate those risks, and implementing cybersecurity solutions, which are the core concepts of risk management as I had learned since the very beginning of my RMSC coursework. As in any job, working at Deloitte Risk Advisory Cyber had its own unique sets of challenges and rewards. The work was fast-paced and challenging and required a high level of attention to detail and up-to-date cybersecurity information. However, the benefits I have gained cannot be neglected. They include exposure to a variety of industries (from local banks to overseas technology companies or even luxury brands), opportunities for professional growth, and the ability to make a positive impact by helping clients to safeguard their valuable data. Besides, Deloitte also provides a platform for employees’ global knowledge exchange, as well as support for certificate-related training.

Risk management science provides a framework and methodology for assessing and managing risks in a variety of contexts, including cybersecurity. By applying risk management principles and techniques to cybersecurity, I can better understand and manage the risks associated with information systems and data. These skills allow me to assist clients to make informed decisions about how to allocate resources and prioritise cybersecurity initiatives.

Throughout my internship, I not only gained cyber knowledge from the company and my beloved colleagues but also realised how important and necessary risk management is in every field, not only in quantitative finance. I’m grateful to be able to study in my faculty and to have been given the chance to work at Deloitte and actually assist a real business using what I have learned.

Hei Ming CHENG

BSc in Risk Management Science
Lund University, Sweden

During the first half of 2017, I experienced a very fruitful semester in Lund University, Sweden. The mathematical statistics courses in Lund University suited my academic needs unexpectedly well. During the time of being an exchange student, I left some of the specific investigation in my major study like investment strategy for a period, and went back to the inevitable fundamentals, statistics and mathematics.

During the training in Lund University, I was introduced into non-parametric inference. I found that the investigation in statistical convergence is very crucial when it comes to different applications like simulation techniques, confidence intervals of parameter estimates and statistical model fitting. Also the study in empirical distribution contributes a lot in survival analysis, actuarial science and non-parametric bootstrap. Only through understanding the mathematics behind can we ensure whether we are using the statistical tools in the correct way and right situation. By learning statistical inference, I believe I am able to take several steps further when I return back to my specific major study.

Besides, I took some courses highly related to my major study, which are Monte-Carlo Simulation and Extreme Value Theory. The simulation course exactly covered the materials which are not taught in the course RMSC4001, such as sequential importance sampling, markov chain monte-carlo and bootstrap techniques. Although it introduced the random number generation and variance reduction techniques in the beginning, most of the contents were still fresh to me. The extreme value course is mostly about modeling the extreme values in 3 different approach, which are block maxima, threshold model and point process, and the relations between their respective statistical distributions.

Last but not least, I took a Swedish introductory course for international students in the very beginning of the semester. I met friends from different countries there and we all agreed that Swedish is a vague language to learn.