Predictive Analytics and Risk Management, MS

Overview

for the Master of Science in Predictive Analytics and Risk Management


Concentrations for this program include:


This degree program is designed to meet the growing demand for professionals with expertise in advanced analytical techniques for risk management across industries such as insurance, consulting, investment, pensions, healthcare, banking, and financial services. The program integrates training in modern statistical methods with principles of actuarial science and financial risk management. It is intended for students with a strong quantitative background who seek careers in predictive analytics for insurance and other financial sectors.

The curriculum provides a multidisciplinary and integrated learning experience. Core requirements include courses from an actuarial science perspective, along with a case study course and an internship course. Students receive training in statistical machine learning, big data techniques, and Bayesian statistical methods. In addition, electives from three related disciplines allow students to tailor the program to their individual educational goals.

The 32-credit-hour program can be completed in one academic year with appropriate course scheduling. Each concentration requires 20 credit hours of coursework organized around three broad areas of expertise, with at least 12 hours completed at the 500 level.

Graduate Degree Programs in Mathematics

Degree Requirements

for the Master of Science in Predictive Analytics and Risk Management


Major Requirements12
Investments and Financial Markets
Predictive Analytics
Risk Analytics and Decision Making
Graduate Internship (or ASRM 490)
Foundations in Risk Management
Required Concentration (Choose one from below):20
Total Hours32
Other requirements (may overlap)
A concentration is required
Minimum 500-level hours required overall12
Minimum GPA3.0

Learning Outcomes

for the Master of Science in Predictive Analytics and Risk Management


Students graduating with an MS degree in Predictive Analytics and Risk Management program will be able to:
  1. Apply statistical learning techniques to analyze big data related to financial and insurance industries.
  2. Use quantitative risk analysis to assess risks and devise creative methods to contain and manage them.
  3. Demonstrate proficiency in using programming software to conduct statistical analysis and visualizations.
  4. Communicate results effectively to technical and non-technical audience.
  5. Participate efficiently in projects that require team collaboration.

Contact Information

for the Master of Science in Predictive Analytics and Risk Management


Actuarial Science and Risk Management

Department Chair: Feng Liang
Program website
Program Office: 264 Computing Application Bldg., MC-382, 605 E Springfield Ave, Champaign, IL 61820
Phone: (217) 300-5630
Email: PARM@illinois.edu

College of Liberal Arts & Sciences

College of Liberal Arts & Sciences website

Admissions

Graduate College Admissions & Requirements
Overview of Program Admissions & Requirements