Course Descriptions

Course Descriptions

The Master of Financial Insurance (MFI) is a unique 12 month professional master’s degree program designed to produce students who will become global leaders in the financial insurance industry. “Finsurance” is a burgeoning field in which sophisticated finance-insurance hybrid products are being developed to meet the needs of an aging global population. Students will acquire expertise in valuing, hedging, and managing the combined financial and insurance risks embedded in such complex products.

The MFI, is currently offered on a full-time basis only, has been developed in response to demand from prospective students and industry members and will fill an important gap in academic training, providing students with the opportunity to bridge their traditional disciplinary backgrounds and develop the connections between these areas.

The program consists of a series of highly cross-disciplinary courses focused on real-world problems, drawing on insurance, finance, statistical and mathematical tools and methods, and delivered in many instances by experienced industry professionals, and a 3.5 month industry internship.

Mandatory Courses

STA 2503 H : Applied Probability for Mathematical Finance ( 0.5 FCE )

This course features studies in derivative pricing theory and focuses on building basic financial theory and their applications to various derivative products. A working knowledge of probability theory, stochastic calculus, knowledge of ordinary and partial differential equations and familiarity with the basic financial instruments is assumed. The topics covered in this course include, but are not limited to: binomial pricing models; continuous time limits; the Black-Scholes model; the Greeks and hedging; European, American, Asian, barrier and other path-dependent options; short rate models and interest rate derivatives; convertible bonds; stochastic volatility and volatility derivatives; currency and commodity derivative.

Letter grade |

STA 2530 H : Applied Time-Series Analysis ( 0.5 FCE )

An overview of methods and problems in the analysis of time series data related to finance and insurance. The course will focus on both theory and application with real datasets using R and Python and will require writing reports. Topics include stationary processes, linear processes; elements of inference in time and frequency domains with applications; ARMA, ARIMA, SARIMA, ARCH, GARCH; filtering and smoothing time-series; and State-space models.

Letter grade |

STA 2535 H : Life Insurance Mathematics ( 0.5 FCE )

This graduate course develops the theory and application of life insurance products. Beginning with basic life insurance and annuity valuation, the course introduces the concepts of premium reserving, multiple decrements, multiple life insurance, and expense loading. As well, topics in pension mathematics will be covered. The course and projects emphasize numerical implementation and practical relevance.

Letter grade |

STA 2550 H : Industrial Seminar Series ( 0.5 FCE )

This course extends over the fall/winter semesters and will feature invited guest speakers delivering both academic and practical seminars on current aspects of finance and insurance modeling, pensions, valuation risk management, regulation and accounting.

Letter grade |

STA 2540 H : Insurance Risk Management ( 0.5 FCE )

This course features studies in the risks, and how to quantify and manage those risk, in financial and mortality linked insurance products. Topics include: hedging of guarantees embedded in equity-linked insurance and annuity products, asset-liability management, determination of regulatory and economic capitals, insurance securitization (life & P/C), longevity bonds and derivatives, reinsurance, catastrophe bonds and derivatives.

Letter Grade |

STA 2551 H : Finance and Insurance Case Studies ( 0.5 FCE )

This course takes cases from a variety of problems in the financial and insurance worlds and students will work in groups to develop both the theory and implementation of cases, write reports and deliver presentations on their findings. The course will be led by industry practitioners. Sample topics include: Solvency II, Pension Benefits Act, valuing and managing complex annuity riders.

Letter grade |

STA 2536 H : Data Science for Risk Modelling ( 0.5 FCE )

This course focuses on data science techniques for risk modelling stemming from finance and insurance, including maximum likelihood estimation, expectation maximization, generalized linear and additive models, mixture models, hidden Markov models, artificial neural networks, and reinforcement learning.

Letter grade |

STA 2546 H : Data Analytics in Practice ( 0.25 FCE )

This course explores what are the various issues that arise when machine and statistical learning methods are used in practice on big data to inform business intelligence (in finance and insurance). In practice, data is not clean, number of features is large, feature engineering must be carried out, and data is often multi-modal consisting not only of structured data, but also of images, text, and social network data. In this course, students will be exposed to various techniques and practical know-how to deal with these cases and learn how to present results to practitioners who are not domain experts.

Letter grade |

STA 2560 Y : Industrial Internship ( 1.0 FCE )

Students will complete an industrial internship or research project in the financial insurance area and write a report, present and defend it.

Letter grade |

STA 2570 H : Numerical Methods for Finance and Insurance ( 0.5 FCE )

This course explores the practical application of various numerical methods to finance and insurance modeling. It covers topics including: the generation of random variables, simulating solutions of stochastic differential equations, variance reduction methods, multi-level sampling, least square Monte Carlo, Markov chain Monte Carlo, and solving partial difference equations stemming from derivative valuation, optimal control, and optimal stopping.

Letter grade |

Elective Courses


Any one of Statistical Sciences’ 0.25 FCE graduate offerings, level 4000 with significant financial, insurance, or data science components, and approval of the MFI Program Director.

Letter grade |