B.Sc. (Hons) Actuarial Science, Computer Science & Artificial Intelligence

Tracks

• AI, Data Science & Actuarial Science

  The integrated AI track: machine learning, data science engineering and actuarial modelling taught as one discipline — from GLMs and gradient boosting through deep learning, causal inference and reinforcement learning, always on insurance data with exposure, censoring and professional standards.

• P&C Analytics

  Ratemaking, reserving and catastrophe risk with modern ML — the CAS route enriched with data engineering and model governance.

• Life, Health & Longevity AI

  Long-term mathematics, pensions and health analytics with deep learning for mortality, morbidity and policyholder behaviour.

• Quantitative Risk & FinTech

  ERM, capital, derivatives and high-performance computing for insurers, reinsurers, asset managers and InsurTech/FinTech builders.

What graduates can do

• Pass SOA Exams P, FM, FAM, SRM and PA (or CAS MAS-I) before graduation, with all three VEE topics satisfied by coursework
• Build production-grade data pipelines and software with tests, version control and cloud deployment
• Design, validate and govern machine-learning and AI systems for pricing, reserving, underwriting and claims
• Quantify and communicate uncertainty with Bayesian, credibility, coherent-risk-measure and decision-theoretic tools
• Act within the Code of Professional Conduct and ASOPs, including fairness and explainability obligations for algorithmic decisions
• Read, reproduce and extend current research at the intersection of actuarial science and AI

Postgraduate: fifth-year M.Sc. and thesis track · Careers: job board · ASA/FSA career roadmap