Quickly and efficiently execute a wide range of models used in bank stress tests and other enterprise-level risk assessments. Significantly reduce the setup time for implementing extremely complex and computationally intensive bank stress test modeling systems.
Streamline model implementation.
A centralized platform and web-based interface simplify the development, deployment and maintenance of even the most complex bank stress test modeling systems (e.g., a Monte Carlo simulation state transition framework). Once you estimate atomic models, you can quickly and easily group them into a system designed to produce desired results. You can reduce the total set-up time for implementing such systems to less than one day – no specialized, non-SAS programming knowledge needed.
Centrally store models.
The SAS Model Implementation Platform stores models in a controlled, central environment, so they are easy to call for execution. Model details are readily viewable, which greatly facilitates transparency. You can search atomic models based on key characteristics. And details on modeling systems are stored in an easily viewable format, making it easy to update and maintain them over time.
Run complex models fast.
Quickly run very complex bank stress test modeling systems at the loan level on millions of loans – even when simultaneously running multiple economic scenarios. Distributed computing on a grid – with our scalable, in‐memory risk engine – allows for massively parallel processing without the need to write distributed processing code. Fast execution means you can spend more time on analysis and exploration, and less time waiting for runs to complete.
Visually explore results.
Once you run a portfolio, you can explore the results at an aggregate level, and then drill down to the loan level in seconds – even with millions of loan-level records. This in-memory drill-down capability enables very detailed, in-depth analysis of bank stress test results. You can explore any level of aggregation on the fly and then export results to an Excel file.
- Fast, efficient model execution. Uses scalable, in-memory technology to quickly process complex loan-level modeling systems for all portfolios across the enterprise.
- Simplified model and group setup. Provides prebuilt model templates and an easy-to-use graphical interface that simplifies the setup and maintenance of complex risk modeling systems.
- Centralized model execution library. Provides a sandbox environment for developing new data models and reports, and keeps all model information centrally stored for easy searching, versioning and tracking.
- Expected credit loss calculation environment. Supports calculation of loan loss models, such as those needed to support the IFRS 9 accounting standard.
- Visual results exploration. Provides the ability to aggregate model results for millions of loans up to any desired level or drill down to the loan level in seconds.
- Integrated part of the SAS Stress Testing suite. Integrates seamlessly with the SAS Stress Testing Workbench and SAS Risk Modeling Workbench to provide a complete solution for transparently orchestrating the entire bank stress test process across all types of risk – market, credit and liquidity.