Financial Insurance

Program Overview

The Department of Statistical Sciences offers a Master of Financial Insurance​​ (MFI), a full-time professional program focused on producing students who will become leaders in the global financial insurance industry. The program stands on three pillars: statistical methods, financial mathematics, and insurance modelling. It provides students with education at the interface of these domains with suff​​icient depth and breadth so that students can provide both detailed analysis of specific financial insurance risks as well as provide a bird’s-eye perspective on how the embedded risks affect the firm enterprise wide.

​This program is particularly appropriate for students with backgrounds in statistics, actuarial science, economics, and mathematics, but students with a quantitative background (such as those in physics and engineering) and sufficient statistical training are also encouraged to apply. The program welcomes applications from international students. For more information, visit the program website​.​

Quick Facts

Master of Financial Insurance

Program Description

The MFI is a full-time professional program based on three pillars: data science, financial mathematics, and insurance modelling. This program is appropriate for students with backgrounds in statistics, actuarial science, economics, and mathematics. Students with a quantitative background (such as physics and engineering) and sufficient statistical training are also encouraged to apply.

Minimum Admission Requirements

• Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Statistical Sciences' additional admission requirements stated below.

• An appropriate bachelor’s degree from a recognized university in a related field such as statistics, mathematics, finance, and actuarial science, or any discipline where there is a significant quantitative component. Studies must include significant exposure to statistics, mathematics, finance, and actuarial science, including coursework in advanced calculus, computational methods, linear algebra, probability, and statistics.

• An average grade equivalent to at least a University of Toronto B+ in the final year or over senior courses; applicants who meet the SGS grade minimum of mid-B and demonstrate exceptional ability through appropriate workplace experience will be considered.

• Three letters of reference including two academic references, one of which should be in a quantitative discipline.

• A curriculum vitae detailing the student’s educational background, professional experience, and skills.

• Applicants whose primary language is not English and who graduated from a university where the language of instruction and examination was not English must demonstrate proficiency in English using one of the official methods outlined in the SGS Calendar.

• Selected applicants may be required to attend an interview.

Admission to the program is competitive, and achievement of the minimum admission standards does not guarantee admission into the program.

Program Requirements

• ​Students must successfully complete 5.5 full-course equivalents (FCEs) as follows:

  • ​Nine required half courses (4.5 FCEs).

  • STA 2560Y Industrial Internship, a four-month summer internship (1.0 FCE). Students must submit a project proposal to the program director and select an advisor by April 15. Students will propose a placement site to be approved by the department. The department will provide approval of the proposal by May 15. An interim report is required by July 7. Students must prepare a final written report and deliver an oral presentation on the internship project at the conclusion of the internship.

​​Required Courses

Fall Session​

Winter Session

Summer Session

⁺ Extended course. For academic reasons, coursework is extended into session following academic session in which course is offered.

Program Length

3 sessions full-time (typical registration sequence: F/W/S)

Time Limit

3 years full-time