Career profile · live from the Careermash careers engine
Careermash
ExploreCareer profile
Actuary
Actuaries use maths and statistics to work out the likelihood of events like illness, accidents or death, then use that to help insurance companies and pension funds make safe financial plans.
Degree usually required
AI impact: medium££££ payUni route
52
AI impact
how much AI is reshaping it
Robin · your guide
Curious about being a actuary? Here's the honest picture - what you'd really do, what you'd earn, and every way in. No need to decide anything yet.
What you'd actually do
As an actuary or actuarial analyst, you use maths and data to help insurance and pension companies make decisions. You look at past data (how many car accidents happen, how long people usually live), use probability and statistics to predict the future, then build financial models to work out what money companies should charge for insurance or save for pensions. You're basically answering the question: 'If we don't know what will happen, how much money is safe to hold back?'
Your work is mostly computer-based and office-based, using specialist software to analyse huge amounts of data and build mathematical models. You'll work with other departments - explaining to bosses what your numbers mean, checking that regulations are being followed, and presenting your findings so non-mathematicians can understand them. You need to be good with numbers and enjoy problem-solving, but you also need to explain complex ideas simply. You'll study for professional qualifications whilst working, which takes several years but leads to well-respected credentials.
1Conduct detailed statistical analyses to evaluate financial risks and uncertainties.
2Develop mathematical models to predict future events and their financial implications.
3Collaborate with underwriters and financial analysts to set premiums and reserves.
4Prepare and present reports that communicate complex actuarial concepts to non-specialists.
5Monitor and review financial data to ensure compliance with regulatory requirements.
6Utilize software tools and programming languages for data analysis and modeling.
7Participate in strategic planning sessions to advise on risk management and financial strategies.
Career progression & pay
01
Getting in
Junior Actuary
£30,000 - £38,000
BSc in Mathematics, Statistics, or a related field
In this entry-level role, you will assist senior actuaries in data analysis and model development, gaining practical experience while working towards your professional qualifications.
02
Building up
Mid-level Actuary
£50,000 - £65,000
3-5 years experience + completion of some actuarial exams
As a mid-level actuary, you will take on more complex projects, lead analyses, and begin to specialise in areas such as pensions or insurance.
03
At the top
Senior Actuary/Head of Actuarial Function
£90,000+
10+ years, chartered/fellow status with the IFoA
In this peak career role, you will oversee actuarial teams, drive strategic initiatives, and play a key role in shaping the organisation's risk management policies.
Degrees that lead here via Mathematical Sciences
Actuarial Mathematics
The University of Liverpool
Actuarial Mathematics with a Year Abroad
The University of Liverpool
Actuarial Science
University of York
Actuarial Science
The University of Essex
Actuarial Science
The London School of Economics and Political Science
Actuarial Science
Queen Mary University of London
Apprenticeships that lead here
Who hires - top UK employers
Aviva
A leading insurance provider in the UK, Aviva offers a dynamic environment for actuaries to thrive and develop their careers.
Lloyd's of London
As a global insurance market, Lloyd's provides actuaries with unique opportunities to work on complex risk assessments.
Aon
Aon is a global professional services firm that offers a variety of actuarial roles across different sectors.
Willis Towers Watson
This multinational company provides a range of actuarial services, making it an exciting place for actuaries to work.
Mercer
Mercer offers actuaries the chance to work on innovative solutions in health, wealth, and career sectors.
AI & the future of this job
Actuarial work sits in genuinely interesting territory: the mathematical and data-crunching layers are highly automatable, but the professional judgement, regulatory accountability, and client-facing advisory dimensions are far more resilient. AI tools are already accelerating model validation, data cleaning, and routine reserving tasks that once consumed junior analysts' time. The profession is not shrinking so much as restructuring, with fewer people needed to do the same volume of technical work, but greater expectation that those who remain can interpret, challenge, and communicate outputs with authority. Students entering this field today need to think of themselves as decision architects, not number processors.
Within 5 Years
Moderate workflow disruption
Over the next five years, AI tools will handle a growing share of routine data preparation, model running, and regulatory reporting drafts. Junior actuarial analysts will find their early-career tasks narrowing, and firms may recruit fewer trainees relative to the workload they process. However, qualified actuaries and those progressing through IFoA exams will remain essential for signing off on models, advising boards, and navigating regulatory scrutiny. The practical effect is a steeper learning curve expectation from day one, with less tolerance for slow ramp-up.
Within 10 Years
Significant role redefinition
By the mid-2030s, AI will likely be running most standard reserving and pricing models autonomously, with humans reviewing outputs rather than building them from scratch. The actuarial role will shift meaningfully towards scenario interpretation, regulatory liaison, ethical oversight of model assumptions, and strategic risk advisory. Firms will need fewer actuaries to maintain the same throughput, but those they employ will operate closer to the boardroom. The IFoA qualification will likely evolve to reflect this shift, placing greater weight on judgement, communication, and model governance skills.
Within 20 Years
Transformed but viable specialism
Two decades out, the boundary between actuary and AI risk strategist will be blurry. The core of the profession, attaching human accountability to probabilistic financial decisions that affect millions of people, will still need qualified professionals, but the shape of training, tooling, and day-to-day work will be unrecognisable compared to today. Climate risk, longevity uncertainty, and emerging liability categories will generate new actuarial demand that partially offsets automation-driven contraction. Those who build careers at the intersection of actuarial science, AI governance, and strategic advisory are well positioned for the long term.
How to stay ahead
Chase the IFoA fellowship, not just the degree
The degree alone is increasingly thin protection in this field. Becoming a fully qualified Fellow of the Institute and Faculty of Actuaries is the credential that carries genuine career resilience, because it represents professional accountability that regulators and clients will continue to demand from humans. Start your exam progression as early as your employer or studies allow.
Build fluency in AI model governance
The actuaries who thrive will be the ones who can critically evaluate AI-generated model outputs, spot flawed assumptions, and articulate risk to non-technical stakeholders. Develop skills in model validation, explainability frameworks, and understanding how large language models and machine learning tools make probabilistic errors. This positions you as the human check on automated systems, which is a durable and well-paid function.
Develop specialist domain depth
Generalist actuarial roles are more exposed to automation than specialists with deep expertise in areas like longevity risk, climate-related financial risk, or cyber liability. These emerging risk categories are complex, data-sparse, and heavily dependent on judgement, making them harder to fully automate and genuinely valuable to employers. Choose a specialism deliberately rather than drifting into general reserving or standard motor pricing.
Invest in communication and advisory skills early
The future actuarial job is closer to a trusted adviser than a technical analyst, and that requires you to be comfortable presenting contested findings to sceptical boards, translating model uncertainty into business language, and influencing decisions without hiding behind the maths. Seek out presentation experience, client contact, and cross-functional project work during your training years, even if it feels peripheral to passing your next exam.
How to get in - your routes
Careermash · your kind of work, the careers in it, and every route in - all in one place.