Financial Risk Analytics
Description
The financial services industry is undergoing significant changes, making the use of data and information technology increasingly important in driving business decisions and managing risk. This course provides a practical introduction to financial risk analytics with a focus on data-driven modeling, computation, and statistical estimation of credit and market risks. Real data case studies will be used throughout the course. Tools from machine learning and statistics will be developed and data sources will be discussed. After taking this course, students will be able to design and implement risk analytics tools in practice.
Prerequisites
MS&E245A or similar, some background in probability and statistics, working knowledge of R, MATLAB, or a similar computational/statistical package.
Topics include
- Mortgage risk
- Asset-backed securities
- Commercial lending
- Consumer delinquencies
- Online lending
- Derivative risk
Course Availability
The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate education section.
