Actuarial science postgraduate personal statement example

Personal statement example

Every January at the savings cooperative where I work, I produce a list of members whose contributions have stopped for six months or more. The first time I did it, I treated it as a filing task. By the third year I had noticed that the list was not random. Members who joined through employer check-off and then changed jobs went quiet within weeks, while farmers who paid in cash after harvest often looked dormant in March and recovered by August. Our rule of flagging anyone silent for six months was treating very different patterns as the same risk. Questions like this, about when something happens as well as whether it happens, are why I want to study actuarial science at postgraduate level.

My first degree was in statistics, and the modules I enjoyed most were probability theory, regression and an introduction to survival analysis. For my final-year project I used an anonymised extract of loan records from a microfinance lender, obtained through my supervisor, to study time to first missed repayment. I built Kaplan–Meier curves for different loan purposes and then fitted a Cox proportional hazards model with loan size, repayment frequency and borrower occupation as covariates. The most useful part of the work was handling censoring properly, since many loans were still running when the data was extracted, and simply excluding them would have made defaults look more common. I checked the proportional hazards assumption with Schoenfeld residuals and found that it held poorly for weekly repayment loans, which I reported rather than ignored. The project received one of the higher marks in my cohort, but I value more that it taught me to question a model before trusting its output. Reading Kleinbaum and Klein's Survival Analysis: A Self-Learning Text alongside my lectures helped me understand the reasoning behind the methods, not just the commands in R.

Since graduating I have worked as a records officer at the cooperative. My job is ordinary but has given me a clear sense of how financial data is created: members' details entered by hand, contributions reconciled against bank statements, loan files that arrive incomplete. I have written spreadsheet checks that catch duplicate member numbers and mismatched dates, and our branch's month-end reconciliation now takes noticeably less time. When the credit committee asked for a summary of dormancy by membership type, I prepared it and explained the seasonal pattern I had seen. I was careful to describe it as an observation from our records, not a forecast, but it led to a discussion about whether farmers should have a longer grace period.

Outside work I keep the books for my aunt's chama, a group of eleven women who contribute monthly and rotate a lump sum. It is small and informal, yet it raises real actuarial questions: what happens to fairness when a member leaves early, and how much should be held back to cover a missed contribution. I have no wish to turn their arrangement into a spreadsheet exercise, but explaining balances clearly to people who trust each other more than they trust paperwork has improved how I communicate numbers.

I also play competitive chess for a club in town. It has nothing to do with insurance, though it has made me comfortable sitting with a difficult position for a long time without rushing.

I am applying now because I can see the limits of what I know. I can fit a survival model, but I want a rigorous grounding in life contingencies, financial mathematics, credibility theory and the professional standards that turn analysis into responsible advice. I have begun working through probability and financial mathematics material independently, and I would like to build towards professional actuarial examinations. In the longer term I hope to work on pricing and reserving for products that serve people like the members on my January list, whose financial lives do not follow a monthly salary.