University of Ljubljana

What you'll study

This programme builds a rigorous foundation in probability, stochastic processes, statistical inference and financial mathematics, then applies those tools to insurance, pensions and risk management. Teaching blends theoretical courses with applied modules and computing practicum, and culminates in an independent master's thesis or research project.

• Core mathematical and statistical modules: probability theory, stochastic processes, measure-theoretic foundations of finance, statistical inference and regression, time series and econometrics.
• Financial mathematics and quantitative finance: derivative pricing and hedging, stochastic calculus, interest rate modelling, credit risk, numerical methods for pricing (finite differences, Monte Carlo, Fourier methods).
• Actuarial science and insurance: life contingencies, survival models, loss distributions and severity modelling, risk theory, reserving and pricing for non-life insurance, pension mathematics and social insurance systems.
• Computing and data tools: practical programming for quantitative finance and actuarial work using Python and R, databases, model implementation, and validation techniques.
• Applied modules and electives: enterprise risk management, Solvency II / regulatory frameworks, financial econometrics, operational risk, machine learning for finance, and internship or industry project options where available.
• Assessment and final project: assessment typically uses a mix of written exams, coursework and projects; the programme concludes with an independent master's thesis or applied project supervised by academic staff.

Entry requirements

Applicants are normally expected to hold a relevant bachelor's degree in mathematics, statistics, actuarial science, quantitative finance, economics, engineering or a closely related quantitative discipline. A strong background in calculus, linear algebra, probability and statistics is required.

• Academic transcripts demonstrating quantitative coursework (calculus, probability, statistics or equivalent).
• Evidence of programming or computational experience is advantageous (examples include coursework, projects, or knowledge of Python, R, MATLAB).
• A personal statement describing quantitative interests and career goals, and one or two academic or professional references.
• Proof of language proficiency where applicable; programmes taught in English require an accepted certificate of English ability unless the applicant has prior education in English.
• Relevant professional experience may strengthen an application but is not usually required for recent graduates.

Career prospects

Graduates are prepared for technical and analytical roles across insurance, banking, pensions, asset management and regulatory bodies. Common career routes include:

• Actuarial analyst or qualified actuary roles in life and non-life insurance, pensions and employee benefits.
• Quantitative analyst or model developer positions in investment banks, hedge funds and asset managers.
• Risk manager or risk modeller roles in corporate risk teams, central banks and supervisory authorities.
• Data scientist or statistical modeller roles where strong probabilistic and computational skills are required.
• Consultancy and advisory positions addressing solvency, valuation, and regulatory compliance.
• Research and doctoral study for those interested in academic or specialised technical careers.

Why study at University of Ljubljana

The University of Ljubljana is the country's leading research and teaching institution, offering access to experienced academic staff with expertise across mathematics, statistics, finance and insurance. The programme benefits from multidisciplinary collaboration, combining theoretical depth with applied projects and industry contacts in Slovenia and Central Europe.

Students also gain from the university's links with local insurance companies, financial institutions and regulatory bodies, which can support internships, applied projects and career networking. Ljubljana itself is a compact, international city with a growing finance and technology sector, making it a practical location for students seeking exposure to regional markets while studying in an academically rigorous environment.