Actuarial Science, Bachelor of Science

In addition to University Requirements:

• Complete individual plan requirements.

Students may be able to use some courses to meet more than one requirement. Contact your advisor for details.

Purpose Statement

Actuarial science is the discipline that measures and manages risk in insurance, finance, and other industries and professions. Students in the Actuarial Science BS study mathematical and statistical foundations, topics such as interest and risk theory, life and health insurance, annuities and pensions, financial modeling, and regression analysis. This is intended as a professional program that leads to employment in the actuarial field.

Coursework prepares students to sit for entry-level exams required for actuarial certification. Along the way, students develop the critical-thinking, analytic, and communication skills necessary to be successful professionals.

Student Learning Outcomes

• Demonstrate competency in mathematics and statistics.
  • Apply calculus concepts, including optimization, univariate and multivariate integrals, as well as partial derivatives, sequences and series, and first-order differential equations to statistical and financial models.
  • Apply matrices, matrix operations, linear equations, and related concepts (e.g., determinants and inverses) to a statistical model.
  • Use probability distributions of random variables to model data and apply rules of probability to derive basic statistical quantities, e.g., expected value and variance.
  • Use software to perform common statistical analyses (e.g., regression, ANOVA, generalized linear models, and time series analysis) and to create and assess graphical summaries.
  • Make model predictions and quantify uncertainty in calculations for a variety of model quantities.
• Demonstrate competency in actuarial science (in some or all, depending on choice of electives).
  • Understand the time value of money in the context of loans, bonds, annuities, and other financial instruments, as well as how to select an optimal portfolio using immunization techniques involving duration and convexity.
  • Select an appropriate probability distribution for a random variable to model risk and loss in the context of insurance.
  • Build actuarial models (life tables, survival models, loss models) and work with mortality, morbidity, or loss distribution datasets.
  • Understand the financial models describing the monetary-world phenomena of random markets, as well as financial instruments and strategies, e.g., derivatives, forwards, futures, options, calls, and puts.
  • Construct parametric models for severity, frequency, and aggregate distributions, estimating associated parameters, and using hypothesis tests or score-based approaches to select a model, as well as conducting valuation and reserving exercises.
• Demonstrate competency in business, economics, and finance.
  • Demonstrate awareness of ethical issues that can occur in a business setting.
  • Analyze supply and demand, consumer behavior, production, and costs; and understand business cycles, fiscal and monetary policy, and global implications of international trade and production.
  • Determine prices in various insurance products and resource markets.
  • Understand internal financial activities, sources of funds, and involvement with money and capital markets.
• Demonstrate mathematical, statistical, and computational reasoning skills.
  • Assess the appropriateness and fit of a model to real-world data and select analysis methods based on the constraints of the study design and the scientific questions of interest.
  • Evaluate the applicability of available mortality and health data to address a desired research question.
  • Assess the statistical significance of components of a proposed model and interpret the results within the relevant situational context.
  • Evaluate the trade-offs of various computational and inferential issues.
• Collaborate with peers and communicate results and issues effectively in preparation for careers in industry, with government agencies, or in academia.
  • Explain computational issues, statistical methodology, and results by both written and oral means to both technical and non-technical audiences.
  • Select and use numerical, graphical, and narrative methods for conveying information to both technical and non-technical audiences.
  • Work effectively on technical teams.
• Be aware of ethical and professional issues in actuarial practice and apply principles of ethical judgment and responsibility when assessing risk and communicating results.
  • Identify ethical and professional issues that arise in actuarial practice.
  • Apply actuarial codes of professional conduct to decision-making and risk assessment.
  • Communicate actuarial analyses responsibly, considering their impact on individuals and society.