Actuarial Science Course

What will I learn?
You will build a thorough command of probability distributions, statistical inference, and life contingencies as they apply to real insurance and financial problems. The course covers loss models, credibility theory, and ratemaking methods used daily by practising actuaries. You will learn how to construct and analyse claims development triangles, apply chain-ladder and Bornhuetter-Ferguson reserving methods, and quantify reserve uncertainty. Advanced topics include economic capital modelling, predictive analytics with generalised linear models and machine learning, and financial economics for valuing embedded insurance options. Computational skills in statistical programming, SQL, and spreadsheet modelling are integrated throughout to support reproducible actuarial workflows.
Elevify advantages
Develop skills
- Loss Modelling and Reserving: Construct aggregate loss models and estimate unpaid claim liabilities accurately.
- Credibility and Ratemaking: Develop actuarially sound insurance rates using credibility weighting techniques.
- Life Contingencies Valuation: Compute net premiums and policy reserves for standard life insurance products.
- Risk Measurement and Capital: Apply Value-at-Risk and Tail Value-at-Risk to assess insurer solvency needs.
Suggested summary
Before starting, you can change the chapters and workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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