In IBM Algorithmics Introduction to Portfolio Credit Risk Engine training course, Participants gain hands-on experience with the portfolio credit risk engine, the Algorithmic component that calculates portfolio credit risk and bottom-up measures of integrated market and credit risks.
By attending IBM Algorithmic Introduction to Portfolio Credit Risk Engine workshop, Participants will learn to:
- Articulate the key data elements required to calculate portfolio credit risk and which Algorithmics' components can provide these inputs
- Define each of the various measures available in PCRE
- Discuss the principles behind the PCRE models
- Generate a typical/sample report based on statistical measures
- List the types of scenario analysis supported within PCRE
- Generate a typical/sample report for scenario analysis
- Launch PCRE Setup Manager and Results Viewer
- Initiate the PCRE controller and workers in a multiprocessor environment
- Knowledge of basic credit risk (e.g. definition of rating, PD and LGD) is essential
- Some portfolio credit risk knowledge would be an asset
This course is aimed at quantitative analysts or capital managers with a credit risk focus; however, the significant hands-on emphasis may also make it of interest to non-quantitative business analysts.