Program Requirements

The Master of Financial Insurance (MFI) program is designed as a 12 month (3 term) program comprised of 8.5 half courses [4.0 full course equivalents (FCEs)], STA 2546 H (0.25 FCE) Data Analytics In Practice, one Statistical Sciences level 4000 graduate course related to finance/insurance (0.25 FCE), and an industrial internship (1.0 FCE). Students proceed through the program as a single cohort, following a common course of study which is fully integrated and computer-laboratory intensive. Course projects and assignments are designed to integrate the material from multiple courses and their application in a real-world practical contexts. Excellence in communication and presentation skills is emphasized in both the oral and written components of the projects.

All core courses ( with the exception of STA 2546 H and the elective STA45** H) in this program are 0.5 FCE which run for twelve (12) weeks and meet for three (3) hours per week (excluding tutorials / computer labs).

The list below illustrates the time-line and collection of courses that students must complete each term.

Term 1: Fall

Applied Probability for Mathematical Finance ( STA 2503 H – 0.5 FCE ) Discrete time modelling, stochastic calculus, financial derivatives: equity, interest rate and commodities, stochastic volatility and jumps.

Applied Time-Series Analysis ( STA 2530 H – 0.5 FCE ) Time series modelling including AR, MA, ARMA, ARCH, GARCH, VAR, co-integration, non-linear models, quantile regression, volatility forecasting.

Life Insurance Mathematics ( STA 2535 H – 0.5 FCE) Life insurance and annuity valuation, premium reserving, multiple decrements, multiple life insurance, expense loading, pension mathematics.

Data Science for Risk Modelling ( STA 2536 H – 0.5 FCE ) Probability and stochastic loss models and estimation, Expectation-Maximization, Bayesian statistics and credibility theory, generalized linear model and predictive modelling, stochastic claim reserving.

Industrial Seminar Series ( STA 2550 HY – 0.5 FCE) Current topics in finance and insurance, e.g., pensions, valuation, risk management, regulation and accounting.

Term 2: Winter

Insurance Risk Management ( STA 2540 H – 0.5 FCE) Insurance & annuity guarantees, asset-liability management, regulatory and economic capital, insurance securitization, longevity bonds & derivatives, reinsurance, CAT bonds & options.

Data Analytics in Practice ( STA 2546 H – 0.25 FCE ) Machine and statistical learning methods; building loss models; techniques and practical know-how to present results to practitioners.

Finance and Insurance Case Studies ( STA 2551 H – 0.5 FCE )Industrial case studies, e.g., Solvency II, Pension Benefits Act, valuing and managing complex annuity riders.

Numerical Methods for Finance and Insurance ( STA 2570 H – 0.5 FCE ) Monte Carlo methods, simulating SDEs, control variates, Brownian bridges, PDEs and finite difference methods.

Industrial Seminar Series ( STA 2550 HY – 0.5 FCE)Current topics in finance and insurance: e.g., pensions, valuation, risk management, regulation and accounting.

Statistical Sciences Elective ( STA 45** H – 0.25 FCE )

Term 3: Summer

Internship

An internship is required for all MFI students. The internship provides a strong experiential learning component and students must complete a detailed report, and deliver a presentation of their findings. Students must complete the following:

Internship project proposal

All students submit a project proposal to the Program Director along with the name of the advisor by April 30. The proposal will be evaluated and modifications will be made if necessary. Final approval is required by May 15.

Interim report

All students submit an interim report to the Program Director by July 7 describing progress in the first half of the summer term.

Final report and presentation

Students must submit a final report describing the details of the project including: the context of the problem, the methods of analysis, the results and interpretation of their analysis. Students must also present their project to an audience consisting of the Program Director, their peers and industry participants.