RISK ANALYTICS AND BEHAVIORAL SCIENCE
Learning to effectively navigate uncertainty is a key issue for all areas of business and especially for those engaged in explicit risk-management activities. The skills for success in these environments include knowing how to formulate the right questions to ask, how to identify the information that is valuable for answering those questions, understanding how to process incoming information to distinguish signal from noise, and how to use that information to put structure to uncertain environments so that one can take good calculated risks. This collective set of skills are at the heart of "decision analysis", which is a structured rational approach to making decisions under uncertainty.
Prerequisites & course information
Requisites: ( R M I 300 or graduate/professional standing) and ( GEN BUS 306 , 704 , 705 , ECON 310 , MATH/STAT 309 , 431 , or MATH 331 ), or declared in the Business Exchange program Course Designation: Core GenEd - Social & Behavioral Science Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Spring 2026 Learning Outcomes: 1. Recognize situations where potential biases in perceptions, understanding, and decisions related to risk management are likely to arise Audience: Both Grad & Undergrad 2. Articulate the behavioral factors and psychological processes that may generate bias in that situation Audience: Both Grad & Undergrad 3. Employ appropriate decision/evaluation process and business analytics to help improve decisions in the face of potential bias. These techniques include Monte Carlo Simulation, Decision Tree Analysis, and Expected Value Maximization Audience: Both Grad & Undergrad 4. Diagnose risk management failures for corporations and suggest techniques and alternative management approaches that could mitigate these risk management issues Audience: Graduate Learning Outcomes: 1. Recognize situations where potential biases in perceptions, understanding, and decisions related to risk management are likely to arise Audience: Both Grad & Undergrad 2. Articulate the behavioral factors and psychological processes that may generate bias in that situation Audience: Both Grad & Undergrad 3. Employ appropriate decision/evaluation process and business analytics to help improve decisions in the face of potential bias. These techniques include Monte Carlo Simulation, Decision Tree Analysis, and Expected Value Maximization Audience: Both Grad & Undergrad 4. Diagnose risk management failures for corporations and suggest techniques and alternative management approaches that could mitigate these risk management issues Audience: Graduate
Sources
- Course catalogue ↗2026-2027