Business, Administration & Tourism

Aktuar/in SAV

You calculate and manage risks for insurance companies and financial markets

Aktuar/in SAV

01 · Overview

What this profession is about

Actuaries analyse insurance risks mathematically, calculate premiums, and secure the financial stability of companies.

In the world of insurance and financial markets, you ensure safety. You use mathematical models and statistical analyses to make uncertain risks calculable. You calculate premiums, check solvency, and develop innovative insurance products. Your expertise protects companies and private individuals from financial losses. You work closely with experts from medicine, technology, and business. Together, you actively shape the future of risk insurance.

FieldBusiness, Administration & Tourism
Education pathSpecialisation / Professional Function
IndustryBanking & Insurance
Swissdoc 0.615.23.0

02 · Salary

What you can earn

MedianCHF 69'918
CHF 58'500CHF 84'500
✓ Strong salary match
Salaries reflect Swiss market data. Range covers entry to senior. Salary reference based on Banquet Chef. Based on 84 observations, updated 7 months ago.

Salary by experience

60k65k70kmedian 70k68k70k62k73k71k60k0-2 yrs3-5 yrs6-8 yrs9-11 yrs12-21 yrs21+ yrs
View as table
ExperienceSalary (CHF)
0-2 yrsCHF 68'000
3-5 yrsCHF 70'326
6-8 yrsCHF 62'218
9-11 yrsCHF 72'800
12-21 yrsCHF 71'324
21+ yrsCHF 60'000

Salary trend

+4% over decade
68k70k68k67k71k70k2014-20162017-20192020-20222023-2025
View as table
PeriodSalary (CHF)
2014-2016CHF 67'600
2017-2019CHF 67'091
2020-2022CHF 70'850
2023-2025CHF 70'000

Top earning cantons

  • ZurichCHF 71'50029 obs.
View as table
CantonSalaryObs.
ZurichCHF 71'50029

Top paying industries

  • Catering / HotelCHF 70'20067 obs.
  • Banking / Financial institutionsCHF 60'0007 obs.
View as table
IndustrySalaryObs.
Catering / HotelCHF 70'20067
Banking / Financial institutionsCHF 60'0007

03 · Pathway

How to enter and grow

Swiss training pathway available in the full profile

  • 🎓 Aktuar/in SAV

Official education path

You enter the profession through a specialised academic or vocational pathway. This route provides solid knowledge in actuarial science and statistics.

Typical training path

Aktuar/in SAV

Prerequisites

  • University degree (Master) in Mathematics or Statistics with a specialization in Actuarial Science
  • Diplom als Pensionsversicherungsexperte /-expertin HFP

Where this can lead

Career changers can often enter the field. This is possible if you already have a degree in mathematics, statistics, or business. You can qualify yourself through specialised courses in actuarial science.

04 · Skills & fit

What it takes

Required skills

  • Mathematical precision
  • Analytical thinking
  • Economic understanding
  • Team-oriented collaboration

Personality fit

  • Swiss career path
  • Career transition
  • Professional growth

05 · Daily reality

What the work feels like

Typical day

You sit at your computer and check complex statistical data. You do this to estimate the probability of future claims accurately. Then you develop new insurance models together with your colleagues. These models must be financially sound and customer-focused.

  • You analyse statistical data to assess insurance risks precisely.
  • You calculate premiums for different groups of people and risk categories.
  • You develop innovative products that meet new market needs.
  • You check the financial solvency of insurance companies.
  • You balance assets and liabilities in asset management.
  • You calculate provisions for future claim payments and pensions.
  • You work closely with doctors, engineers, and economists.

Working conditions

You usually work in the offices of insurance and reinsurance companies, pension funds, or state supervisory authorities. Your workplace is defined by computer-based data analysis and close professional exchange with other experts.

Strengths

  • Mathematical precision
  • Analytical thinking
  • Economic understanding
  • Team-oriented collaboration

Trade-offs

  • High responsibility
  • Continuous further training
  • Complex data sets
  • Regulatory pressure

06 · Similar

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