Jocelyne Jusuf
BSc in Risk Management Science
Reinsurance Group of America
During my actuarial internship at Reinsurance Group of America (RGA), I had the opportunity to work closely with the Regional Valuation Team and to contribute to actuarial systems development and US GAAP LDTI reporting. My tasks included cashflow reconciliation, data analysis, and supporting the AXIS software to improve actuarial processes.
One major project I worked on was the “Improvement in AXIS for Principle-Based Initiatives (PBI)”. This set of initiatives is used each year when submitting to the regulator for compliance and for evaluating the company’s financial and risk management. Hence, my team aimed to streamline scenario testing and improve the efficiency of applying assumptions to the best-estimate dataset. The project involved consolidating datasets and optimising assumptions to reduce run time and human error. I also worked on the “Reserve Impact Calculator” and its checking files, which assesses reserve changes and financial projections. In this process, issues such as the “New Business Tagging Issue” and unnatural data movements were identified. Overall, this template helped to improve data accuracy and consistency.
I also contributed to the development of training materials for incoming interns, focusing on SQL, Excel, and LDTI principles, to ensure a smooth transition into actuarial tasks.
The support from my mentors at RGA was an important factor in my work, and their guidance helped me navigate complex actuarial tasks. The RMSC courses I took provided me with an understanding of statistics and financial knowledge, and studying RStudio was essential for learning SQL and other software tools. The analytical and problem-solving skills I developed through those courses enabled me to quickly grasp SQL and adapt to new tools at work. I am grateful for the experience and the opportunity to apply my academic knowledge in a professional setting, which has greatly enhanced my technical and industry skills.
Pascal Sun
BSc in Risk Management Science
Risk Analytics Stream
FWD Group Holdings Limited
I was delighted to be given the opportunity to work as an Investment Risk Intern under Group Risk at FWD Insurance. This internship provided me with hands-on experience in market risk analysis and risk-reporting optimisation, which strengthened my technical and professional skills.
My key responsibilities included daily market risk monitoring related to FWD’s investment portfolio, which was summarised into a bi-weekly report that was submitted to the manager. I conducted risk analyses of the Asian markets using Bloomberg and Reuters, focusing on FWD’s diversified portfolio, and categorised these by investment types, countries, holding periods, etc. I tracked key risks such as political instability, monetary/fiscal policy changes, and volatilities in fixed-income securities. These insights were critical for assessing the potential impacts on the portfolio.
I also used Python for risk-reporting automation, and particularly the Pandas and NumPy libraries. These tools enabled me to efficiently cleanse and consolidate data and thus contributed to operational excellence. For example, I used Python to finish a task that involved converting multiple value-at-risk (VaR) reports from business units across Asia into a structured Excel sheet. In addition, to reduce inconsistency in risk reporting across different business units, I used Excel VBA and Power BI to build new workflows and establish interactive dashboards. This improved the effectiveness of risk reporting by including new features such as timely alerts regarding investment limit breaches.
The knowledge and skills I have learned from the Risk Management Science programme were important factors in the success of the internship. The statistics and finance courses equipped me with the analytical skills necessary to assess risks and understand market dynamics. The experiential learning activities, ranging from Bloomberg terminal training to company visits, not only broadened my views and skillsets but also helped me establish my real interests in my university life. I am also very grateful for the excellent academic and career support from the RMSC Programme and the Department of Statistics.
Johnny Chou
BSc in Quantitative Finance and Risk Management Science
J.P. Morgan
This summer, I participated in J.P. Morgan’s Global Markets programme, where I rotated between two teams. During the programme, I was tasked with various coding projects, using VBA to optimise team workflows and Python to backtest different options trading strategies. I also made pitches on J.P. Morgan’s Quantitative Investment Strategies offerings and participated in various types of ad hoc projects.
Prior to this, I also gained valuable experience through a macro sales internship at ING Bank and a part-time derivatives trading development internship at HKEX. These roles allowed me to deepen my understanding of market dynamics and derivative products, complementing my work at J.P. Morgan.
Through these experiences, I was able to apply the technical knowledge I acquired from the QFRM programme, which includes courses in Finance, Statistics, and Risk Management Science. This foundation enabled me to better understand diverse structured products and cross-asset solutions, allowing me to make more meaningful contributions to the teams I worked with. I received a return offer and will be a new Global Markets Analyst at J.P. Morgan next year.
Winson Kwong
BSc in Quantitative Finance and Risk Management Science
Hong Kong Monetary Authority (HKMA)
During the summer, I successfully completed an internship at HKMA. Through this internship, I discovered the reporting process and how investment decisions are made from a portfolio management perspective. By applying the data analytics and financial markets knowledge acquired through my study programme, I was able to contribute to the automation of reports to streamline the workflow. Moreover, the programme’s emphasis on inquisitiveness allowed me to be more proactive, build relationships, and broaden my perspective by interacting with colleagues inside and outside my team.
Moreover, the courses I took from various departments allowed me to refine my technical skills. As part of the RMSC4002 course – Financial Data Analysis with Machine Learning, my teammates and I used techniques such as random forest and PCA in projects. This proved useful during job interviews with my future employers. Furthermore, the finance and statistics courses allowed me to acquire solid knowledge of financial products and the identification of underlying market trends. This will undoubtedly be crucial for my future career in finance and will allow me to access positions with quantitative responsibilities.
