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SAS® Model Implementation Platform: Solution Overview
4h 2m + Hands-On Practice
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SAS® Model Implementation Platform: Solution Overview
RMIP : 
This course prepares model implementation teams in financial institutions to conduct credit loss reserving and loan valuation to satisfy regulatory requirements, including IFRS9 and CECL.
Learn How To
  • Import portfolio data and macroeconomic variables.
  • Create and modify atomic models, including ASTORE and Python models, using SAS Risk Model Editor.
  • Validate that a model is producing the same results as it did during the model estimation process.
  • Write and apply logic to calculate specified output variables.
  • Group models into model groups by asset type.
  • View and analyze portfolio run results.
  • Dynamically create shocked scenarios to evaluate the impact of changes in economic and portfolio variables on model results.
  • Conduct attribution analyses to analyze the differences between two analysis runs by making incremental, sequential changes.
  • Analyze current portfolio data and new volume projections.
  • Publish models to a modeling system.
    • Who Should Attend
    Members of model development and implementation teams in financial institutions who are responsible for activities such as stress testing, credit loss reserving, and loan valuation required to satisfy regulatory requirements
    Prerequisites
    Before attending this course, you should have experience using the SAS programming language. Expertise in statistical modeling concepts and methods is also required.
    SAS Products Covered
    SAS Model Implementation Platform;SAS Risk Management
    Course Outline
    Getting Started with SAS Model Implementation Platform
  • Introduction.
  • Overview. Creating Input Data Sets
  • Overview of input data sets.
  • Portfolio data set requirements.
  • Economic data set requirements.
  • Risk data object requirements.
  • Function set requirements.
  • Counterparty data set requirements.
  • Mitigation data set requirements. Working with Model Data Sets
  • Model requirements.
  • Implementing atomic models.
  • Model unit testing.
  • Model overrides data set requirements. Creating Portfolio Analysis Objects
  • Creating model groups and model group maps.
  • Additional processing methods.
  • Copying portfolio analysis objects. Submitting and Analyzing Analysis Runs
  • Submitting an analysis run.
  • Viewing analysis results.
  • Using modeling systems.
  • Troubleshooting.Additional Topics
  • Working with ASTORE models.
  • Working with Python models.
  • Using model sensitivity analysis.
  • Using mitigation.
  • Creating a scenario run with backtesting.
  • Performing attribution analyses.
  • New originations generation.
  • Cash flow analysis.
    • Live Class Schedule
    Duration: 13.0 hours
    Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
    This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
    Private Training
    Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
    Request private training
    Mentoring Services
    Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.
    Request mentoring