2026-2027 Course Catalog

Source: https://catalog.illinois.edu/graduate/las/predictive-analytics-risk-management-ms/enterprise-risk-management/ Parent: https://catalog.illinois.edu/graduate/

for the Master of Science in Predictive Analytics and Risk Management, Enterprise Risk Management concentration

Prepares students for the nascent profession of predictive analytics; it provides background and skill sets for data analytics with focus on financial and insurance industries. A student successfully finishing the program will typically have acquired a broad foundation of machine learning and predictive modeling techniques to forecast outcomes and glean valuable insights that can lead to better-informed business and investment decisions.

The assessment of the above-stated learning objectives will include:

the job placement/graduate school acceptance rates
feedback from employers
graduate satisfaction surveys

These assessments will be conducted on an annual basis. We conduct exit surveys on all students each year, which should provide data on graduate students’ job placement and graduate school acceptance rates. On the survey we will design questions to assess student’s overall evaluation of these learning objectives. The curriculum was developed in close collaboration with industry partners. We expect to maintain close relationship with them and seek their feedback on the quality of our graduates on a regular basis.

Graduate Degree Programs in Mathematics

for the Master of Science in Predictive Analytics and Risk Management, Enterprise Risk Management concentration

Course List

 | Code | Title | Hours |

| --- | --- | --- | | Core Requirements (12 hours): | | | | FIN 530 | Foundations in Risk Management | 2 | | ASRM 410 | Investments and Financial Markets | 4 | | ASRM 539 | Risk Analytics and Decision Making | 2 | | ASRM 555 | Advanced Predictive Analytics | 4 | | Concentration Required Courses (see below) | | 12 | | Electives (see below) | | 8 | | Total Hours | | 32 |

Other Requirements

Course List

 | Code | Title | Hours |

| --- | --- | --- | | Other requirements may overlap | | | | A concentration is required. | | | | Minimum 500-level Hours Required Overall: | | 12 | | Minimum GPA: | | 2.75 |

Enterprise Risk Management Concentration

Course List

 | Code | Title | Hours |

| --- | --- | --- | | Required Courses: | | 12 | | FIN 526 | Investment Banking | | | FIN 537 | Financial Risk Management | | | ASRM 533 | Risk Management Practices and Regulation | | | Electives: | | 8 | | Choose two of the following: | | | | ASRM 409 | Stochastic Processes for Finance and Insurance | | | ASRM 499 | Topics in Actuarial Science | | | ASRM 510 | Financial Mathematics | | | ASRM 539 | Risk Analytics and Decision Making (if not taken as a core requirement) | | | ASRM 561 | Loss Data Analytics & Credibility | | | ASRM 569 | Extreme Value Theory and Catastrophe Modeling | | | ASRM 575 | Life Insurance and Pension Mathematics | | | ASRM 595 | Advanced Topics in Actuarial Science and Risk Analytics | | | FIN 431 | Property-Liability Insurance | | | FIN 511 | Investments | | | FIN 512 | Financial Derivatives | | | FIN 513 | Advanced Financial Derivatives | | | FIN 514 | Valuation of Complex Derivative Securities | | | FIN 515 | Fixed Income Portfolios | | | FIN 519 | Behavioral Finance | | | FIN 551 | International Finance | | | FIN 580 | Special Topics in Finance (Big Data Analytics) | | | FIN 590 | Individual Study and Research | | | MATH 563 | | | | STAT 542 | Statistical Learning | | | STAT 590 | Individual Study and Research | |

for the Master of Science in Predictive Analytics and Risk Management, Enterprise Risk Management concentration

Department Chair: Feng Liang\ Unit website\ 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