What it means
The core idea is that individual events are unpredictable but large groups are not. Nobody knows which of 12,000 drivers will crash next year, yet the proportion who do is remarkably stable, and that stability is what makes insurance possible.
Actuaries estimate both how often an event happens and how expensive it is when it does. Their work runs through three main fields: general insurance, life insurance and pensions.
Increasingly they also appear in banking, healthcare and climate risk, wherever long-dated uncertainty has to be valued today. The qualification is one of the longest in professional life, often taking six or more years of examinations alongside full time work.
For a manager without a finance background, the practical point is that an actuarial number is an estimate with assumptions built into it. Change the assumed investment return, life expectancy or claims inflation and the answer moves substantially, sometimes by tens of millions on a large pension scheme.
Asking which assumptions drive the result is usually more useful than asking for the result on its own. Pension work shows this most clearly.
A defined benefit scheme promises payments decades into the future, and the actuary discounts those promises back to a value today, which then sits on the sponsoring company's balance sheet. A small change in the discount rate can swing that liability enough to alter reported profit and the room available to pay dividends.
Actuarial reserving also drives insurer solvency. Set reserves too low and the insurer looks profitable right up until claims arrive; set them too high and capital is trapped earning very little, so regulators watch the balance closely.
In practice
Real-world examples.
Example
A manufacturer with a closed defined benefit pension scheme receives a triennial valuation showing a deficit of $18,000,000, up from $6,000,000 three years earlier. Almost all of the change comes from a lower discount rate rather than from anything the company did.
Example
A pet insurer uses claims data by breed, age and postcode to set premiums, and finds that claims frequency roughly doubles after a pet's eighth year. Premiums are restructured to rise with age instead of staying flat, which stops younger policyholders subsidising older ones and leaving.
Example
A regional insurer buys reinsurance covering losses above $10,000,000 from a single storm. The actuarial team models a one in two hundred year event at $46,000,000, and that figure sets both the amount of cover bought and the capital the regulator requires.
Think of it
“Actuarial science is the math of risk-using statistics to understand uncertainty.
Formula
Calculation
Expected claims cost = number of policies x probability of a claim x average claim size, and the gross premium then adds a loading for expenses and profit.
A motor insurer covers 12,000 policies. Historic data suggests 4% of policyholders make a claim in a year, and the average claim settles at $9,000.
Expected claims = 12,000 x 0.04 x $9,000 = 480 claims x $9,000 = $4,320,000. Spread across the book, the pure risk premium is $4,320,000 / 12,000 = $360 per policy.
If expenses and profit are to make up 25% of premium income, the gross premium is $360 / 0.75 = $480 per policy. Total premiums are then 12,000 x $480 = $5,760,000, and the loading is $5,760,000 - $4,320,000 = $1,440,000, which is exactly 25% of $5,760,000.Case study
Seen in the real world.
This illustrative case involves a fictional company. Calder Mutual Insurance, an invented regional insurer, priced its household policies using a simple rule: last year's claims plus 5%. For several mild years this worked, and the fictional board treated the growing surplus as evidence of good underwriting.
A new actuarial team rebuilt the pricing from the ground up, separating claims frequency from claim severity and modelling flood exposure by property rather than by region. The analysis showed that around 8% of policies in low lying areas carried an expected claims cost of roughly four times the premium being charged, while suburban policies were being overpriced and steadily lost to competitors.
Calder repriced across two renewal cycles, declined to renew the most exposed properties without a significant premium increase, and bought additional reinsurance. When a serious flood arrived two years later, the illustrative outcome was a difficult year rather than an insolvency.
Watch out
Common mistakes.
- Treating an actuarial valuation as a precise fact rather than an estimate that shifts whenever the underlying assumptions are updated.
- Confusing an actuary with an accountant, when one prices and reserves for future uncertainty and the other records and reports what has already happened.
- Reacting to a pension deficit as though it were an immediate cash demand, when the recovery plan is usually spread over many years.
Questions
People also ask.
Why do pension liabilities move so much from one valuation to the next?
Because they are the present value of payments decades away, so small changes in the discount rate or life expectancy produce large changes in the total.
Do only insurers and pension schemes employ actuaries?
No, they increasingly work in banking, healthcare, product warranty pricing and climate risk, anywhere long term uncertainty has to be valued today.
What should a non-specialist ask when handed an actuarial report?
Ask which three assumptions have the biggest effect on the answer and how the number would change if each moved in an unfavourable direction.
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