MSc in Actuarial and Financial Engineering postgraduate personal statement example

Personal statement example

Each September I rebuild the fixtures spreadsheet for the junior hockey league where I referee on Saturday mornings. Twelve teams, three pitches and a handful of volunteer umpires have to fit around school holidays and one club that cannot play before ten. It is a small scheduling problem, but doing it every year has made me comfortable with the kind of work I enjoy most: turning a messy set of constraints into something that holds up when real people depend on it. I want to apply that habit to the quantitative modelling of insurance and financial risk, and I am applying for postgraduate study in actuarial and financial engineering to build the rigour that work requires.

My degree in Mathematics and Statistics gave me a solid base in probability, linear algebra and real analysis, alongside modules in generalised linear models, stochastic processes and numerical methods. The stochastic processes course was where I first saw Markov chains used to describe movement between states, such as healthy, ill and deceased, and I found it satisfying that a transition matrix could carry so much practical meaning. I achieved a 2:1 overall, with my strongest marks in statistical modelling and my weakest in pure analysis, which I have since revisited through self-study because I know measure-theoretic probability underpins much of financial mathematics.

My final-year project used survival analysis on an anonymised dataset of gym membership cancellations provided by a local leisure centre. I fitted Kaplan–Meier curves and a Cox proportional hazards model in R to see whether contract type and joining month were associated with earlier cancellation. The most useful part was checking the proportional hazards assumption with Schoenfeld residuals and finding it did not hold for contract type, which led me to stratify the model instead. I learned that a clean output is not the same as a defensible one, and that explaining the assumptions to my supervisor clearly mattered as much as the code.

Since graduating I have worked as a claims handling assistant at a pet insurance company. I log new claims, check policy terms and exclusions, request vet records and pass complex cases to senior handlers. I am not involved in pricing, but the job has shown me how product design meets reality: waiting periods, annual limits and pre-existing condition clauses all shape the claims I see. I have noticed, for example, how many claims for older dogs arrive close to policy renewal, and it has made me curious about how insurers account for ageing portfolios and lapse behaviour, which links back to the survival models I built at university. I also helped my team lead tidy a weekly report in Excel so that pending claims were grouped by age, which reduced the time we spent chasing overdue cases.

Alongside work I have been preparing for more advanced study. I worked through the early chapters of John Hull's Options, Futures, and Other Derivatives, and replicated the binomial tree pricing of a European option in Python to check that I understood risk-neutral valuation rather than just the formula. I have also started reading on the Solvency II framework to understand why capital requirements are framed around a one-year horizon.

Outside work and study, refereeing has taught me to make quick decisions calmly and to explain them to annoyed parents, and I manage the shared spreadsheet for a car-share arrangement between my parents and my aunt, splitting fuel and insurance costs fairly by mileage.

I am looking for a programme that combines actuarial theory, financial mathematics and serious computational work. I bring a reliable statistical foundation, practical exposure to how insurance operates day to day, and steady, careful working habits, and I am ready to be stretched by the more demanding mathematics this field requires.