BSc Actuarial Science
A rigorous undergraduate programme blending probability, statistics, finance, and professional actuarial practice. Earn exemptions from IFoA CM1, CM2, CS1, CS2, CB1, and CB2 examinations while building real-world modelling skills in Excel and R.
What You Will Study
The BSc Actuarial Science programme provides a thorough grounding in the mathematical and statistical foundations required for a professional actuarial career. You will study financial mathematics, life and general insurance, risk theory, and professional practice across three focused years.
- Year 1: Core mathematics, probability, financial mathematics, and introductory statistics form the analytical foundation.
- Year 2: Life contingencies, actuarial statistics, and general insurance principles with professional case studies.
- Year 3: Advanced risk theory, derivative pricing, actuarial modelling in R and Excel, and an industry-linked dissertation project.
- Exemptions: Successful graduates gain exemptions from IFoA/SOA subject papers CM1, CM2, CS1, CS2, CB1, and CB2.
Programme Highlights
D'Math University's actuarial science programme is built around the IFoA Core Technical and Core Principles syllabi, ensuring every graduate enters the profession with maximum exam credit and practical readiness.
- Professional Alignment: Curriculum co-designed with IFoA and SOA guidelines for maximum exam exemption eligibility.
- Industry Placements: Optional Year-in-Industry sandwich placement with leading insurers, consultancies, and pension funds.
- Software Training: Excel VBA, R, and introductory Python for actuarial data analysis and modelling.
- Global Pathways: Articulation agreements with partner universities in the UK, USA, Canada, Australia, and Singapore.
- Mentorship: One-to-one pairing with qualified Fellows of the IFoA (FIA) from Year 1.
Financial Mathematics
Time value of money, annuities, yield curves, bond valuation, and interest rate risk — aligned with IFoA CM1.
Actuarial Statistics
Statistical inference, Bayesian credibility, generalised linear models, and survival analysis for actuarial applications (CS1/CS2).
Life Contingencies
Life tables, multi-state models, net and gross premium calculations, policy values, and profit testing (CM1 extension).
General Insurance (GI)
Claims reserving, IBNR techniques, pricing GLMs, reinsurance structures, and catastrophe modelling fundamentals.
Derivative Pricing
Forwards, futures, options, Black-Scholes framework, the Greeks, and binomial tree pricing models (CM2).
Risk Theory
Collective and individual risk models, ruin theory, aggregate loss distributions, and reinsurance optimisation.
Corporate Finance
Capital structure, WACC, dividend policy, M&A mathematics, and financial statement analysis (CB2).
Actuarial Modelling
Spreadsheet modelling in Excel VBA, actuarial simulation in R, and data wrangling for real insurance datasets.
Click any course to view its objective and learning outcomes.
ACS 101 Probability for Actuaries +
Objective
To establish the probabilistic foundation required for actuarial modelling.
Learning Outcomes
- Apply probability axioms and conditional probability to actuarial scenarios.
- Compute moments, generating functions and tail probabilities.
- Identify and use distributions common in insurance modelling.
- Derive joint and marginal distributions for dependent risks.
- Simulate random variables to estimate probabilities numerically.
ACS 102 Financial Mathematics +
Objective
To introduce the time-value of money and standard financial instruments.
Learning Outcomes
- Compute present and future values under simple and compound interest.
- Construct and interpret yield curves.
- Value bonds, annuities and loan schedules.
- Evaluate net present value and internal rate of return for projects.
- Apply duration and convexity to interest-rate risk.
ACS 103 Life Contingencies I +
Objective
To model future lifetime random variables and basic life insurance products.
Learning Outcomes
- Construct and interpret survival functions and life tables.
- Compute premiums for whole-life and term assurance products.
- Calculate reserves using prospective and retrospective methods.
- Apply the equivalence principle to price contracts.
- Adjust for select and ultimate mortality.
ACS 104 Survival Models +
Objective
To extend life-contingency methods to general survival data.
Learning Outcomes
- Estimate survival functions using Kaplan-Meier and Nelson-Aalen.
- Fit parametric survival distributions including Weibull and Gompertz.
- Apply Cox proportional-hazards regression.
- Interpret hazard rates and cumulative incidence functions.
- Account for censoring and truncation in survival data.
ACS 201 Risk Theory +
Objective
To analyse aggregate insurance losses and ruin probabilities.
Learning Outcomes
- Model frequency and severity using compound distributions.
- Compute moments and tails of aggregate loss distributions.
- Apply the Cramér-Lundberg model for ruin probabilities.
- Calibrate ruin models to observed claim data.
- Evaluate reinsurance arrangements for ruin reduction.
ACS 202 Loss Distributions +
Objective
To fit and interpret heavy-tailed distributions used in non-life insurance.
Learning Outcomes
- Estimate distribution parameters by maximum likelihood.
- Compare candidate models with goodness-of-fit tests.
- Apply Pareto, Lognormal and Generalised Pareto distributions.
- Estimate Value-at-Risk and Expected Shortfall.
- Adjust loss data for inflation and trend.
ACS 203 Investment & Asset Models +
Objective
To build models of asset returns and apply them to actuarial problems.
Learning Outcomes
- Apply geometric Brownian motion to asset price modelling.
- Estimate volatility from historical data and option prices.
- Construct portfolios using mean-variance optimisation.
- Model interest-rate term structures with Vasicek and CIR.
- Discuss model risk in long-horizon projections.
ACS 204 Pensions & Insurance Practice +
Objective
To apply contingency theory to occupational pensions and group insurance schemes.
Learning Outcomes
- Compute member benefits in defined-benefit and defined-contribution plans.
- Project pension liabilities under demographic assumptions.
- Apply funding and accounting valuations.
- Discuss regulatory frameworks governing pensions.
- Evaluate de-risking strategies including buy-ins and buy-outs.
ACS 301 Stochastic Calculus for Finance +
Objective
To introduce continuous-time stochastic processes used in modern finance.
Learning Outcomes
- Apply Brownian motion and Itô calculus to derivative pricing.
- Derive the Black-Scholes equation and its solutions.
- Use martingale methods to value contingent claims.
- Solve simple stochastic differential equations.
- Discuss the limits of arbitrage-free pricing.
ACS 302 Credibility Theory +
Objective
To balance individual experience with collective data when setting premiums.
Learning Outcomes
- Apply Bühlmann and Bühlmann-Straub credibility models.
- Compute credibility weights from data.
- Use Bayesian credibility for parameter updating.
- Apply empirical Bayes estimators to portfolios.
- Compare classical and modern credibility approaches.
ACS 303 Reserving Methods +
Objective
To estimate outstanding insurance liabilities under uncertainty.
Learning Outcomes
- Apply chain-ladder and Bornhuetter-Ferguson methods.
- Compute Mack and bootstrap reserve uncertainty.
- Allow for inflation, large losses and recoveries.
- Evaluate the impact of reserving choices on solvency.
- Document reserving assumptions for audit and regulator review.
ACS 304 Professionalism, Ethics & Practice +
Objective
To prepare students for professional actuarial work and the regulatory landscape.
Learning Outcomes
- Identify the responsibilities of actuaries to clients and the public.
- Apply professional standards on technical work and disclosure.
- Discuss ethical dilemmas using established frameworks.
- Communicate technical results to non-actuarial audiences.
- Maintain continuing professional development records.
AND OR NOT XOR -> <->
Actuarial Trainee
Join leading insurers such as Aviva, AXA, Swiss Re, and Zurich on structured graduate schemes with fast-track qualification support.
Risk Analyst
Quantify, model, and report on financial, operational, and insurance risks within banks, insurers, and consultancies.
Insurance Analyst
Price products, assess claims patterns, and build reserving models for general and life insurance portfolios.
Pension Consultant
Advise trustees and sponsors on defined benefit pension valuations, investment strategy, and regulatory compliance.
Reinsurance Analyst
Model catastrophe exposures, structure reinsurance treaties, and support underwriting decisions at global reinsurers.
Financial Mathematician
Apply advanced mathematical tools to derivative pricing, portfolio construction, and risk measurement in capital markets.
Why D'Math University — Our 4-Step Approach
Foundation Mastery
We ensure every student masters the mathematical and statistical core before advancing to professional actuarial subjects, preventing gaps that slow qualification progress.
Exam-Aligned Teaching
All modules are explicitly mapped to IFoA and SOA syllabus objectives. Past paper practice, mock exams, and examiner-led workshops are embedded throughout.
Industry Immersion
Regular guest lectures from qualified actuaries, live case studies from partner firms, and an optional placement year embed students in the profession from Year 1.
Global Career Launch
Our careers team and alumni network spanning 40+ countries help graduates secure roles in London, New York, Singapore, Toronto, and Sydney within three months of graduation.
Speak to an adviser — admissions@dmathu.ac | IFoA exemption assessment included