Actuarial Science
The Rize Actuarial Science program equips students with the skills needed for modern actuarial work by combining mathematics, statistics, data science, and programming. Developed in collaboration with industry experts, the curriculum focuses on practical preparation for the first two actuarial exams while avoiding unnecessary coursework. With added flexibility for electives and liberal arts exploration, this program produces well-rounded graduates ready to contribute on day one in a variety of quantitative fields.
Actuarial Science
Courses
Foundations of Data Analytics I
In an increasingly data-driven world, everyone should be able to understand the numbers that govern our lives. Whether or not you want to work as a data analyst, being “data literate” will help you in your chosen field. In this course, you’ll learn the core concepts of inference and data analysis by working with real data. By the end of the term, you’ll be able to analyze large datasets and present your results.
Foundations of Data Analytics II
This course is intended as a continuation of Foundations of Data Analytics I. In this course, you’ll conduct more advanced analysis and data manipulation using spreadsheets. You will also expand your data analytics toolkit by learning the basics of the programming language Python, enabling you to solve a wider range of data problems. Additionally, this course introduces predictive models.
Mathematical Theory of Interest
Actuaries focus on using math and statistics to evaluate risk and make strategic decisions. This course covers a range of topics relevant to actuaries, including measurement of interest rates, interest theory, and the pricing of bonds, mortgages, annuities, and other financial instruments. This course will also fully cover all content required by the Society of Actuaries Financial Mathematics (FM) Exam and its equivalents.
Actuarial Science and Risk Management with R
This course focuses on team-based problem solving in actuarial science & risk management. Students will learn the fundamentals of the R programming language, RStudio and R Markdown, and use these tools as well as the software package Excel to complete a range of projects. Projects vary, but may include bond and loan amortization, analysis of the efficient frontier and the capital asset pricing method, insurance liability & estimates of expected loss. This course culminates in a capstone project that ties together skills from throughout the Actuarial Sciences program.
Probability for Actuaries
Actuaries and quantitative professionals deal primarily in probabilities. This course will cover a wide range of topics and introduce you to core probability concepts needed for actuarial and quantitative work. You will be able to apply concepts of probability to real-world scenarios. This course will also fully cover nearly all content required by the Society of Actuaries Probability (P) Exam and its equivalents.
Student Outcomes
Learning Outcomes
- The student will understand and apply various interest algorithms to different financial investments, both qualitatively and quantitatively.
- Demonstrate advanced critical thinking, problem solving and programming skill in order to solve open ended data based problems.
- Apply advanced statistical tools in R in order to build robust and scalable risk models.
- Possess robust qualitative and quantitative skills in the use of probability concepts and techniques.
Certifications
- Society of Actuaries "P" exam
This program prepares students for an exam testing knowledge of probability concepts and their application to risk modeling. It covers topics like general probability, random variables, and distributions—foundational skills for actuarial work.
- Society of Actuaries "FM" exam
This program prepares also prepares students for an exam focusing on financial mathematics principles, including interest theory, annuities, loans, bonds, and general financial instruments. It emphasizes the mathematics used in finance and insurance calculations.
Disclosure
This program includes courses delivered online through an institution of the Lower Cost Models Consortium (LCMC), however all academic credit applies toward the degree requirements at your degree-granting institution.
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