Program Overview

Bachelor of Science in Actuarial Science

The Bachelor of Science in Actuarial Science is a comprehensive program that covers a wide range of topics in mathematics, statistics, computer science, and finance. The program is designed to provide students with a solid foundation in the principles of actuarial science and to prepare them for careers in the field.

Course Descriptions

• MATH 115 - Differential Calculus (3 (3,0,0)): An introductory course focusing on limits, derivatives, and their applications, including tangent lines, critical points, optimization, and continuity.
• STAT 111 - Statistics and Probability (3 (3,0,0)): Provides actuarial students with a solid foundation in the fundamental concepts and methods of statistics and probability theory.
• CS101 - Computer Programming I (4 (4,0,2)): Teaches programming concepts through Java including variables, control structures, data types, methods, arrays, and file operations.
• MATH 117 - Integral Calculus (3 (3,0,0)): Covers fundamental concepts of integrals, techniques of integration, and their applications such as areas, volumes, work, arc length, and surface area of revolution.
• STAT 112 - Statistical Inference and Regression Analysis (4 (4,0,0)): Advanced course focusing on inference and regression methods for actuarial practice.
• ACSC 492 - Cooperative Training (10 (10,0,0)): Seven-month cooperative training in local/international organizations with structured work plan and performance evaluation by host and university.
• FIN 210 - Principles of Finance (3 (3,0,0)): The course is an introduction to the principles of finance, including fundamentals of financial reporting, financial environment, financial statements, taxes and cash flow, interest rates and time value of money.
• MATH 223 - Linear Algebra (3 (3,1,0)): Examines the techniques of linear algebra including matrices, determinants, systems of linear equations, vector spaces, eigenvalues, eigenvectors, and linear transformations.
• ACSC 249 - Introduction to Data Science (3 (3,0,0)): Covers foundational topics in data science including data manipulation, statistical analysis, machine learning with Python, and visualization using Matplotlib.
• STAT 219 - Introduction to Stochastic Analysis (3 (3,0,0)): Introduces stochastic processes and calculus for actuarial applications in risk assessment and financial analysis.
• ACSC 241 - Financial Mathematics (4 (4,0,0)): Covers interest theory, annuities, bonds, loans, cash flow analysis, yield rates, convexity, duration, immunization, and interest rate swaps.
• ENG 301 - Technical Writing (3 (3,0,0)): Focuses on technical writing principles for professional contexts including document design, report writing, and analytical writing skills.
• ACSC 253 - Actuarial Corporate Finance (3 (3,0,0)): Covers corporate finance with focus on capital budgeting, valuation, dividend policy, CAPM, financial markets and instruments, and firm value optimization.
• ACSC 381 - Actuarial Contingencies I (3 (3,0,0)): Introduces survival models, life insurance, annuities, and actuarial methods relevant for professional exams.
• ACSC 361 - Actuarial Science Problem Lab I (1 (0,2,1)): Hands-on training using MATLAB Financial Toolbox for financial modeling, risk analysis, and portfolio optimization.
• STAT 311 - Time Series and Applications (3 (3,0,0)): Teaches ARMA/ARIMA models, Fourier analysis, state space models, and time series analytics using R or Python.
• ACSC 383 - Actuarial Contingencies II (4 (4,0,0)): Covers benefit premiums, reserves, multi-life/multi-decrement models, and applications in Takaful.
• ACSC 362 - Actuarial Science Problem Lab II (1 (1,0,0)): Develops C++/Python skills for actuarial computations in life and non-life insurance applications.
• ACSC 363 - Enterprise Risk Analysis (4 (4,0,0)): Covers risk models, reinsurance, loss distribution, and approximation techniques including moment generating functions and limiting distributions.
• ACSC 441 - Mathematics of Financial Derivatives (3 (3,0,0)): Focuses on pricing financial derivatives, including options, forwards, risk management, and continuous/discrete models.
• ACSC 473 - Loss Models (3 (3,0,0)): Examines aggregate claims distribution, ruin theory, credibility models, Poisson surplus processes, and empirical Bayes methods.
• ACSC 450 - Ethics for Actuaries (3 (3,0,0)): Explores ethics in actuarial practice including professional standards, conflicts of interest, and confidentiality.
• ACSC 444 - Advanced Topics in Insurance Management (3 (3,0,0)): Studies insurance operations, underwriting, regulation, marketing, and liability coverage.

Program Structure

The program is designed to provide students with a comprehensive education in actuarial science, including coursework in mathematics, statistics, computer science, and finance. The program also includes cooperative training and hands-on labs to provide students with practical experience in the field.