Occupation intelligence

actuarial assistant

Snapshot

Interested in a career blending mathematics, statistics, and finance? As an actuarial assistant, you'll play a vital role in assessing risk and helping organizations make informed decisions about insurance and financial products.

Summary

Actuarial assistants are essential members of actuarial teams, supporting qualified actuaries in their work. Your days will involve analyzing statistical data, conducting research, and assisting in the development of premium rates and insurance policies. You’ll use statistical formulas and models to evaluate potential risks like accidents, injuries, and property damage, contributing to the financial stability of organizations.

Key responsibilities
  • • Gathering and analyzing statistical data from various sources.
  • • Assisting in the development and testing of actuarial models.
  • • Preparing reports and presentations summarizing findings and recommendations.
Labour market

Where this occupation is in demand

Reported labour shortages and surpluses, by year. Published for occupation groups, not for individual job titles.

Shortage reportedSurplus reportedReported in another yearNot covered by this source

Deeper colour: reported the same way in more consecutive years.

Figures cover Business and administration associate professionals — 200 jobs including this one.

3 of 8 in shortage202521 of 32 growing4.2Mopenings to 2035

In shortage: Germany, Italy, Netherlands.

Longest-running shortage: Netherlands, 4 years.

Select a place on the map to see its figures.

About this source

Source: ELA/EURES labour shortages and surpluses. Readings are published at occupation-group level, and cover Europe. Editions differ in annex layout and country coverage, so a change between years does not always mean the labour market changed. Countries in grey were not reported, which is not the same as being in balance.

What these words mean

The four things this section reports

Reported demand
Whether employers report needing people in this job — a judgement published by a national or EU body, not a count.
Where it is heading
Which way employment in this job is expected to move over the coming years, from an official projection.
Openings
Roughly how many openings arise — from growth and from people leaving the job.
Typical pay
What people in this job typically earn where the source publishes it. Blank does not mean unpaid; it means nobody publishes it for that place.

A measure is left out when nobody publishes it for that place, rather than shown as zero.

Which way the market leans for you

In your favour
More openings than people looking — employers are competing for candidates.
Balanced
Openings and candidates are roughly matched.
Competitive
More people looking than openings — expect to compete.
Mixed evidence
Sources disagree, or the same occupation group is short in one part and oversupplied in another.

Every source resolves to one of these four, so there is a single vocabulary to learn. What differs is the evidence behind it, which is printed underneath each verdict — a measured ratio of openings to jobseekers, or an assessment published by a national body.

How this job compares with other jobs in the same country

Strong
Among the strongest in that country
Good
Stronger than most jobs in that country
Mixed
About typical for that country
Weak
Weaker than most jobs in that country

This is a rank within one country, not a score you can carry across borders — the registers behind two countries count different people, so the same number means different things in each. It is also why a job can be among the strongest in a country and still show as Competitive: it leads the field in a market that is crowded overall.

Where these come from

Every figure is published by a national statistics office, a public employment service or an EU body, and each card names its source and the period it covers. Some places are counted monthly, others assessed once or twice a year, so two places on the same map can be describing different moments — the date is always shown.

None of this predicts one person's chances. It describes a market.

Explore More

Find your career path and explore the science behind our recommendations.

Quick fit check

Could actuarial assistant fit you?

Answer three quick questions. This is not a full assessment — it is a teaser to help you decide whether to compare your profile.

Progress0/3

Do you enjoy tasks that require Analytical Thinking?

Do you enjoy tasks that require Attention to Detail?

Do you enjoy tasks that require Integrity?

NexFuture™

Future Outlook for actuarial assistant

The outlook for actuarial assistant reflects a balanced mix of automation exposure and durable, human-led work.

How are these scores calculated?

The Resilience Score (0–100) estimates how structurally protected this occupation is from automation and AI disruption, based on task-level analysis. Higher scores mean more human-judgment-intensive tasks. AI Exposure shows the estimated percentage of task hours that current AI capabilities could affect. These are model-derived structural indicators, not predictions about individual job security.

Play the future

How could actuarial assistant change as AI adoption grows?

Several task areas may shift toward AI-assisted workflows, so reskilling becomes more important.

Significant task-level transformation is estimated in 6 years (around 2032) under the selected Expected Pace scenario.
~0%
Resilience
Automation Risk
EXP~100%
Human advantage
MOAT~0%

Illustrative scenario based on task automatability — not a forecast. Values are rounded the further ahead you look.

2026
2029
2037
AI Adoption Speed:

How AI may change this role

Deterministic, model-based interpretation of current role signals — not a guarantee of replacement.

Human-owned 5% Human-owned
What still depends on people

Most tasks here are AI-assistable rather than purely human-led.

The Human Edge To stay ahead in this role, focus on actuarial science and financial markets. These human-centric skills are the hardest for AI to replicate in the next 20 years.
Assist 35% Assist
Where AI may become a co-pilot
  • apply statistical analysis techniques
  • carry out statistical forecasts
  • analyse market financial trends
Automate 94% Automate
Tasks most exposed to automation
  • obtain financial information
  • compile statistical data for insurance purposes
  • calculate insurance rate
Detailed Analysis

Vital Signs & AI Vectors

AI Exposure Vectors

0-100%
AI / Machine Learning 35%

Exposure to AI-assisted analysis, pattern recognition, and predictive modelling tasks

Cognitive Software 12%

Exposure to workflow automation, decision-support software, and process digitisation

Generative AI 2%

Exposure to content generation, creative augmentation, and large language model tools

Robotic & Physical Automation 0%

Exposure to physical automation, robotics, and sensor-driven task displacement

Technical Details
Methodology: NexFuture v3.0 Sources: O*NET® 30.3, ESCO v1.2.1 Updated: Aug 2026

NexFuture v3.0 estimates automation exposure natively from ESCO essential-skill groups, weighted by skill mass and calibrated against expert anchors. Scores are probabilistic estimates, not guarantees. See the NexFuture Methodology White Paper for full details.

Measures automation exposure. It does not measure pay, demand, or how many jobs exist near you.

Day in the life

What people in this role usually do

Financial Services

Day in the life

A typical day as a actuarial assistant

09
09:00 · Morning
calculate insurance rate
Gather information on the client's situation and calculate their premium on the basis of various factors such as their age, the place where they live and the value of their house, property and other relevant assets.
10
10:30 · Mid-morning
compile statistical data for insurance purposes
Produce statistics on potential risks such as natural and technical disasters and production downtimes.
12
12:00 · Midday
analyse market financial trends
Monitor and forecast the tendencies of a financial market to move in a particular direction over time.
14
14:00 · Afternoon
apply statistical analysis techniques
Use models (descriptive or inferential statistics) and techniques (data mining or machine learning) for statistical analysis and ICT tools to analyse data, uncover correlations and forecast trends.
15
15:30 · Late afternoon
carry out statistical forecasts
Undertake a systematic statistical examination of data representing past observed behaviour of the system to be forecast, including observations of useful predictors outside the system.
17
17:00 · Wrap-up
obtain financial information
Gather information on securities, market conditions, governmental regulations and the financial situation, goals and needs of clients or companies.

Task order is illustrative. Individual days vary.

Software & Technologies & Knowledge areas
Software & Technologies
A programming language APLAvidian Technologies ProphetBenfield ReMetricaBentley MicroStationC#C++Corel WordPerfect Office SuiteDatabase softwareData visualization softwaredBASEGGY AXISGoogle Workspace softwareHarvard GraphicsHyland OnBase Enterprise Content ManagementIBM Lotus 1-2-3IBM SPSS StatisticsInsightful S-PLUSMicrosoft AccessMicrosoft Active Server Pages ASPMicrosoft Excel
Knowledge areas
  • actuarial science

    The rules of applying mathematical and statistical techniques to determine potential or existing risks in various industries, such as finance or insurance.

  • principles of insurance

    The understanding of the principles of insurance, including third party liability, stock and facilities.

Cross-sector skills
  • financial markets
  • statistical analysis system software
  • statistics
Essential skills
performing calculations
  • calculate insurance rate

    Gather information on the client's situation and calculate their premium on the basis of various factors such as their age, the place where they live and the value of their house, property and other relevant assets.

monitoring financial and economic resources and activity
  • analyse market financial trends

    Monitor and forecast the tendencies of a financial market to move in a particular direction over time.

analysing and evaluating information and data
  • apply statistical analysis techniques

    Use models (descriptive or inferential statistics) and techniques (data mining or machine learning) for statistical analysis and ICT tools to analyse data, uncover correlations and forecast trends.

gathering information from physical or electronic sources
  • obtain financial information

    Gather information on securities, market conditions, governmental regulations and the financial situation, goals and needs of clients or companies.

analysing scientific and medical data
  • carry out statistical forecasts

    Undertake a systematic statistical examination of data representing past observed behaviour of the system to be forecast, including observations of useful predictors outside the system.

entering and transforming information
  • compile statistical data for insurance purposes

    Produce statistics on potential risks such as natural and technical disasters and production downtimes.

Skill DNA

Skill DNA

Work personality traits and values that define this role

Key traits you need
Analytical Thinking Attention to Detail Integrity Dependability Achievement/Effort Initiative Persistence Adaptability/Flexibility Cooperation Independence Leadership Stress Tolerance Innovation Self-Control Concern for Others Social Orientation
Key rewards you can expect
AchievementWorking Condit…RecognitionRelationshipsSupportIndependence
Career progression

Growth Pathways & Similar Roles

Explore typical career progression paths, adjacent skills, and similar roles to plan your next transition.

Career landscape

Where does actuarial assistant fit?

This role
actuarial assistant This role

Similarity scores based on skill overlap from ESCO data.

Common questions

Frequently asked questions

What skills are most important for an actuarial assistant?
Strong analytical and mathematical skills are crucial. Proficiency in statistical software (like R or SAS) is highly valued, as is attention to detail and the ability to communicate complex information clearly.
Is this a good career path for someone without a traditional actuarial science background?
Yes! While a degree in mathematics, statistics, or a related field is common, individuals with strong quantitative skills from other disciplines can transition into this role. Many employers offer on-the-job training and support for professional development.
What is the typical work arrangement for an actuarial assistant?
This occupation is primarily an employment-based role. You'll typically work as an employee within an insurance company, consulting firm, or financial institution.
Actuarial Assistant — is there a shortage in Europe?
No. In the 2025 ELA/EURES edition, a surplus was reported in 5 of the 8 European countries that assessed this occupation group: Greece, Finland, Latvia, Sweden and 1 more. 3 countries reported a shortage. These assessments are published per occupation group rather than per job title.
Actuarial Assistant — what does it pay in the United States?
$51,440 a year at the median, as of 2025-05. State medians run from $27,490 to $82,580. Source: US Bureau of Labor Statistics. This is a United States figure and not a projection for Europe.