SAS Allowance for Credit Loss Features List
Data quality
- Configurable data quality rules for checking data and visualizing quality reports.
- Automated data quality fixes based on rules, respecting data versions.
Model execution
- Choice of model source and engine: Highly efficient SAS Risk Engine, Base SAS, Python, etc.
- Wide range of model types, including low-code/no-code and user-written code.
Manual adjustments
- Rule-based adjustments and allocations, individual assessment; flexible and fully governed through audit trail and comments.
Stage allocation
- Stage allocation rules for flexible and transparent process (for IFRS9).
Attribution allocation
- Fully governed calculation, allowing the analysis of all movements at the individual position level.
- Sophisticated approach, enabling the comparison and explanation of results from different periods, models, scenarios and parameters.
- Intuitive interface-based configuration, with no need to write code or parameters.
- Users can choose economic risk factors and portfolio attributes to be analyzed individually or grouped into buckets.
Simulations cycle
- The whole process can be executed on different portfolios, scenarios and parameters, enabling you to run what-if analyses and compare different results.
Workflow & governance
- Workflow orchestrates executions and facilitates collaboration during the entire IFRS9/CECL process.
- Fully governed and auditable process allows for the repeatability of all process steps.
- Objects and logic segregation.
- Multitenancy is at application and namespace levels.
- Integration with GIT allows for a full logic versioning.
- Batch processing allows for full or partial process automation.
Efficiency
- Data is stored in a governed and efficient database.
- Storing all data versions, intermediate results and adjustments guarantees full data auditability and calculation traceability.