Actuarial Science, Artificial Intelligence and Information Systems, MIS

The actuarial profession is undergoing rapid transformation due to technological advancement.Traditional actuarial work is being augmented and in many cases fundamentally reshaped by artificial intelligence and information systems. Industry trends reveal that AI and machine learning are revolutionizing core actuarial functions including pricing, reserving, and risk assessment.

The Master of Interdisciplinary Studies: Actuarial Science, Artificial Intelligence, and Information Systems Concentration directly addresses these market needs by providing comprehensive actuarial science knowledge aligned with professional credential requirements, while simultaneously developing information technology and advanced AI skills specifically focused on actuarial applications. Students gain hands-on experience with modern AI tools and systems, and learn to integrate actuarial and AI concepts through applied projects. This integrated approach prepares graduates for the increasingly technical demands of modern actuarial work.

Upon completion of this concentration, students will be able to:
1. Apply actuarial principles to solve complex risk assessment problems
2. Develop and implement analytics solutions that are suitable for insurance data
3. Integrate actuarial science and AI systems concepts in practical applications

Degree Requirements

Admission Requirements: The program is designed to accommodate students at various stages- from fresh STEM graduates to working non-actuaries pivoting to actuarial science or early career actuaries having made some progress toward their actuarial credential who seek further actuarial training and AI systems upskilling.

All admitted students should have:
• Three semesters of Calculus (MATH 2211, 2212 and 2215, or equivalent)
• Two semesters of Mathematical Statistics (MATH 4751 and 4752, or equivalent)
• An Introduction to Programming course (CIS 3260, or equivalent)

Program Curriculum: The proposed program structure includes 10 courses: seven required core courses plus three electives. The core courses ensure competency in both actuarial fundamentals and AI systems, while electives allow specialization in areas of interest.

Required Courses (21 hours)

AS 8140 - Probability 3 Credit Hours
or
AS 8360 - Loss Modeling and Ratemaking 3 Credit Hours
AS 8230 - Financial Mathematics 3 Credit Hours
or
AS 8340 - Life Contingencies 3 Credit Hours
ECON 8740 - Applied Statistics and Econometrics 3 Credit Hours
RMI 8300 - Predictive Risk Modeling 3 Credit Hours
or
RMI 8450 - Machine Learning in Actuarial Science and Risk Management 3 Credit Hours
CIS 8005 - Data Programming for Analytics 3 Credit Hours
or
MSA 8010 - Data Programming for Analytic 3 Credit Hours
CIS 8080 - Information Systems Security and Privacy 3 Credit Hours
CIS 8600 - Generative AI for Business 3 Credit Hours

Electives (9 credit hours)

Select three courses (9 hours) from the following list:

AS 8340 - Life Contingencies 3 Credit Hours
or
AS 8360 - Loss Modeling and Ratemaking 3 Credit Hours
AS 8350 - Advanced Life Contingencies 3 Credit Hours
or
AS 8430 - Advanced Loss Modeling 3 Credit Hours
RMI 8350 - Enterprise Risk Management 3 Credit Hours
RMI 8400 - InsurTech: New Technologies in Insurance Markets 3 Credit Hours
MSA 8770 - Text Analytics 3 Credit Hours
CIS 8085 - Information and Information Systems Security Risk Management 3 Credit Hours
CIS 8398 - Advanced AI Topics in Business 3 Credit Hours
CIS 8684 - Cyber Threat Intelligence 3 Credit Hours
CIS 8795 - IT Infrastructure for Big Data 3 Credit Hours
Other elective courses with the approval of the Program Director in the M.R. Greenberg School