SAS Risk Management vs. SAS Risk Modeling
A side-by-side comparison based on G2 review data.
| Metric | SAS Risk Management | SAS Risk Modeling |
|---|---|---|
| Overall rating | 4.3 | 4.2 |
| Review count | 98 | 12 |
| Ease of use | 8.3 | 8.3 |
| Ease of setup | 7.8 | 8.3 |
| Quality of support | 8.7 | 8.7 |
| Meets requirements | 8.7 | 8.7 |
| NPS | 55.208333 | 50 |
| Small Business | 24.0% | 25.0% |
| Mid-Market | 39.6% | 25.0% |
| Enterprise | 36.5% | 50.0% |
| Total page views | 345 | 12 |
| Total LLM citations | 1,395 | 21 |
SAS Risk Management
Profitability. Efficiency. Regulatory compliance. No matter how your financial institution prioritizes risk, SAS has proven methodologies and best practices to help you establish a risk-aware culture, optimize capital and liquidity, and meet regulatory demands. Put on-demand, high-performance risk analytics in the hands of your risk professionals to ensure greater efficiency and transparency. Strike the right balance between short- and long-term strategies. And confidently address changing regulatory requirements.
- Features
- Ease of Use
- Implementation Ease
- Solution Efficiency
SAS Risk Modeling
SAS Risk Modeling delivers an integrated infrastructure to handle data, build models using traditional statistical methods as well as advanced machine learning techniques, backtest the model, and implement them quickly providing a more flexible risk modeling solution than any outsourcing alternative. With SAS Risk Modeling, modelers can create open, explainable models in a well-managed and controlled environment. And they can do it for their regulatory risk, business models and using the latest analytic techniques, such as artificial intelligence (AI) and machine learning.
- Implementation Ease
- Ease of Use
- Analytics
- Features