Predictive Analytics and Risk Management: Financial and Insurance Analytics, MS
Overview
for the Master of Science in Predictive Analytics and Risk Management, Financial and Insurance Analytics concentration
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.
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Degree Requirements
for the Master of Science in Predictive Analytics and Risk Management, Financial and Insurance Analytics concentration
Courses will be scheduled so that students may complete the 32-hour program in one academic year. Each concentration requires 12 hours of common core courses, organized around three broad areas of expertise, including a case study course. Each concentration also requires 12 hours of related area coursework specific to the concentration, plus an additional 8 hours of electives from a prescribed list included in this proposal. At least 12 hours must be taken at the 500 level.
| Code | Title | Hours |
|---|---|---|
| Major Requirements | 12 | |
| Investments and Financial Markets | ||
| Predictive Analytics | ||
| Risk Analytics and Decision Making | ||
| Graduate Internship (or ASRM 490) | ||
| Foundations in Risk Management | ||
| Code | Title | Hours |
|---|---|---|
| Financial and Insurance Analytics Concentration Requirements | 12 | |
| Generalized Linear Models | ||
| Applied Bayesian Analysis | ||
| Data Science Programming Methods | ||
or STAT 480 | Big Data Analytics | |
| Financial and Insurance Analytics Concentration Electives | 8 | |
| Choose two of the following: | ||
| (FIN elective credits are capped at 8 credits per student) | ||
| Actuarial Statistics II | ||
| Stochastic Processes for Finance and Insurance | ||
| Statistics for Risk Modeling I | ||
| Statistics for Risk Modeling II | ||
| Loss Models | ||
| Casualty Actuarial Mathematics | ||
| Life Contingencies I | ||
| Actuarial Research | ||
| Topics in Actuarial Science | ||
| Financial Mathematics | ||
| Risk Management Practices and Regulation | ||
| Advanced Predictive Analytics | ||
| Loss Data Analytics & Credibility | ||
| Risk Modeling and Analysis | ||
| Extreme Value Theory and Catastrophe Modeling | ||
| Life Insurance and Pension Mathematics | ||
| Advanced Topics in Actuarial Science and Risk Analytics | ||
| Property-Liability Insurance | ||
| Investments | ||
| Financial Derivatives | ||
| Advanced Financial Derivatives | ||
| Valuation of Complex Derivative Securities | ||
| Fixed Income Portfolios | ||
| Behavioral Finance | ||
| Financial Risk Management | ||
| Enterprise Risk Management | ||
| Big Data Analytics in Finance for Predictive and Causal Analysis | ||
| International Finance | ||
| Statistical Data Management | ||
| Data Science Programming Methods (If not taken as concentration requirement) | ||
| Big Data Analytics (If not taken as concentration requirement) | ||
| Topics in Computational Statistics | ||
| Statistical Learning | ||
| Advanced Time Series Analysis | ||
| Individual Study and Research | ||
| Total Hours | 32 | |
| Code | Title | Hours |
|---|---|---|
| Other requirements (may overlap) | ||
| A concentration is required | ||
| Minimum 500-level hours required overall | 12 | |
| Minimum GPA | 3.0 | |
Learning Outcomes
for the Master of Science in Predictive Analytics and Risk Management, Financial and Insurance Analytics concentration
Students graduating from the Financial and Insurance Analytics concentration of the Predictive Analytics and Risk Management program will be able to:
- Apply statistical learning techniques to analyze big data related to financial and insurance industries.
- Demonstrate proficiency in programming and software used to conduct statistical analysis and visualizations.
- Communicate effectively technical findings to a wide range of audience.
- Participate efficiently in case studies and internships that require team collaboration.
Contact Information
for the Master of Science in Predictive Analytics and Risk Management, Financial and Insurance Analytics concentration
Actuarial Science and Risk Management
Department Chair: Feng Liang
Unit 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