I studied pure mathematics in my undergraduate degree but was already interested pursuing a career as an actuary. I became an intern in a life insurance company as an actuary and later became a full-time employee after graduation.
In my experience, life insurance products tend to have complex and long policy terms, which become a challenge for actuaries to quantify the risks and calculate the optimum premium and reserves. I found this challenging yet fun because the problem could vary every time and the products themselves are getting more innovative, which brings a whole new level of calculation complexity. These are the reasons I wanted to pursue my career as an actuary in the life insurance industry.
I decided to continue learning by studying the Cass MSc Actuarial Science. I wanted to increase my mathematical and statistical skills, with a focusing on the actuarial field, as well as broaden my knowledge of the applications of actuarial science.
Cass is well-known for its MSc Actuarial Science programme. The School offers broad and varied accredited actuarial science modules which allows students up to six actuarial exam exemptions. The assessment in most modules are a real-life application and are carried out using essential software such as R, VBA and Excel. In addition, there are also options for student to take business analytics modules which is really what got me really interested in the first place and helped me decide where to study.
The Future of Actuaries
The ever-growing trend of business digitalisation is pushing a lot of companies to require people with technical skills related to big data platforms and automation. Companies will need more people with the ability to analyse large amounts of raw data, manipulate it, and create an algorithm to transform it into something functional for the company to then visualise the result. That is where a business analyst plays an important role.
While it is true that business analysts are needed in every sector, in the financial sector and the insurance and investment industries, business analysts require a combination of strong data analysis skills as well as the ability to quantify future risks. In these cases, an actuary can fulfil these requirements.
Combining actuarial science and business analytics: preparing for my future career
What I think will be the most useful technique of business analysis for my career is machine learning. As an actuary, I will be dealing with a lot of data to make some assumptions out of it to predict future risks. It became a much more challenging thing in life insurance where actuaries were required to predict long-term future risks based on historical data. Machine learning could help clean the data by predicting missing values or even predict new variables using unsupervised techniques.
Frequent analysis of the data is also common for actuaries, whether it is to calculate monthly reserve, performance monitoring, or premium re-calculation for Yearly Renewable products. Machine learning could speed up the process by fitting all of the analysis models and validate the result much quicker.
Muhammad Alhavif, MSc Actuarial Science (2020)
*From September 2020, Cass Business School will be launching the MSc in Actuarial Science with Business Analytics pathway, which prepares students for the non-traditional actuarial field of business analytics.