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Actuary interview questions (2026)
Researched, current questions asked in real actuary interviews (Finance & Accounting), with what a strong answer actually does. Questions marked 2026 are the newer, AI-era questions employers now ask.
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What they assess
- Actuarial & statistical modelling
- Problem solving
- Explaining complexity
- Study & exam discipline
- Commercial awareness
The questions to expect
Walk me through how you'd price a simple term assurance product. What assumptions matter most?
Mortality, lapses, expenses, investment return, margin — and say which the price is most sensitive to and why. Structure over precision at interview.
What's the difference between best-estimate and prudent assumptions, and when is each appropriate?
Best-estimate for realistic planning and pricing; prudence (margins for adverse deviation) for reserving and solvency. One sentence each, then an example.
An insurer's motor book is losing money. How would you investigate whether it's pricing, claims experience or business mix?
Structure it: loss ratios by segment and cohort, frequency vs severity trends, mix shift against plan. Say what data you'd pull first — method is the marks.
Tell me about explaining a technical result to a non-actuarial audience.
The profession's known weakness is communication — show you're the exception. What you simplified, what you refused to oversimplify, and the decision it enabled.
Describe a piece of analysis where your first approach didn't work.
Show the pivot: how you diagnosed why it failed, what you tried next, and the check that convinced you the second answer was right. Dead ends handled well impress.
Tell me about a time you questioned the assumptions behind a model you were given.
Healthy scepticism is core actuarial instinct. Show what looked off, how you tested it, and how you raised it without torching the model's owner.
Tell me how you've balanced intense study or professional exams alongside full-time work.
IFoA exams take years — they're asking if you'll last. Concrete routines (study days used well, spaced revision, exam plans) reassure far more than determination talk.
Why actuarial work rather than another quantitative career like data science or quant finance?
Have a real comparison: the structured profession, the insurance problems, judgement over pure prediction. Naming what you're giving up makes the choice credible.
How do you see machine learning changing actuarial work, and what are the risks of using it in pricing?2026
Better risk segmentation, but watch explainability, bias and regulatory fairness rules. An actuary's edge is judging when a model shouldn't be trusted — say that.
Walk me through the three financial statements and how they link together.
Net income tops the cash flow statement; ending cash lands on the balance sheet; net income also flows to retained earnings. Practise it aloud in under 90 seconds.
What's the difference between profit and cash flow, and why does it matter?
Accruals versus cash timing. Give one concrete example — a profitable firm failing on cash because debtors pay late — and you've shown real understanding.
Tell me about a time you found an error or discrepancy in financial data. What did you do?
Show your method: how you spotted it, traced the cause, corrected it, and what control you added so it can't recur. The control is the impressive part.
Preparation notes
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Turn this into a plan
A list of questions is a start; a programme is what changes the outcome. Intervooh builds a day-by-day plan for your exact actuary interview — company research, story building with an AI coach, spoken practice with delivery feedback, and scored mock interviews.