SAS Risk Modeling
Quickly develop, validate, deploy and track risk models in–house while minimizing model risk and improving model governance.
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Make well-informed risk decisions
Reduce losses and boost your overall business performance by making better, data-driven risk decisions in, for example, loan originations, account management and collections processes. In addition, SAS Risk Modeling enables you to develop risk models for virtually all lending products – including credit cards, installment loans, mortgages and commercial loans.
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Adopt a sustainable, auditable model development environment
A user-friendly graphical interface boosts productivity and efficiency, enabling you to easily create data sets, derive variables and manage judgmental models. You can work collaboratively, share variables, and apply filters and other parameters to maintain corporate IP and reduce your model risk. In addition, you have the flexibility to reuse existing SAS code.
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Easily access and manage data
Access, transform, standardize and cleanse all relevant data to create a 360-degree view of the customer or counterparty. A solution-specific data model lets you build robust, easy-to-access data structures that ensure consistency, powered by integrated data extraction, householding and deduplication, mapping and loading capabilities.
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Quickly develop risk models in-house
Develop, validate and implement an unlimited number of risk models in-house with our end-to-end, integrated solution. You'll get risk models into production faster while reducing your model risk. The solution also includes champion/challenger capabilities, which enable low-risk experimentation, leading to better-performing models.
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Lower costs with support for multitenancy
SAS Risk Modeling supports multitenancy on a single SAS Viya deployment. Multitenancy separates business units within single or multiple corporations while sharing resources, thus lowering costs.
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Process data in SAS CAS
Because SAS Risk Modeling is powered by SAS Cloud Analytic Services, it performs modeling and scoring with its highly parallel and distributed architecture. SAS Risk Modeling supports in-memory processing for data-intensive tasks that include building modeling analytical base tables, backtesting, scoring analytical base tables, actual calculation, and ongoing monitoring of statistical calculation models.
Key features
Superior risk data collection & management
Gives you easy access to all prerequisite third-party bureau, application, billing-payment and collections data from multiple data sources.
Fast, flexible scorecard development
Enables rapid in-house development, validation and implementation of risk models in a collaborative environment.
Unequaled performance reporting
Provides a wide selection of web-based model stability, performance (model monitoring), calibration and model-input validation reports, including those suggested by BCBS Working Paper 14.
Powerful, user-friendly interface
Lets you create models faster and reduce training costs with GUI-based data management, modeling data set creation, data mining and reporting tools.
Parameter sharing
Enables you to share parameters, such as derived variables, filters, binning schemes, data mining projects and notes to retain corporate IP while reducing staff churn and human resource risk.
In-database processing
Provides the advantage of powerful in-database processing capabilities for dealing with very large data sets.
Ability to combine machine learning & open source with traditional models
Lets you develop, deploy and monitor innovative machine learning models alongside traditional risk models within the same integrated environment.
Chartis RiskTech100® 2026 Awards
SAS ranks No. 2 overall – with seven category wins
SAS is ranked second overall in the world's foremost ranking of the Top 100 risk management and compliance technology providers. SAS also bested seven technology award categories, including AI for Banking, Balance Sheet Risk Management, Behavioral Modeling, Capital Optimization, Enterprise Stress Testing, IFRS 9 and Model Risk Management.
Related products, solutions & capabilities
- SAS for Risk Modeling & Decisioning | Powered by AzureModernize risk across the organization with a trusted solution for managing analytical models and decision strategies.
- SAS® Credit OriginationSimplify credit onboarding with an AI-powered platform that automates decisions, orchestrates data and integrates analytics in real time.
- SAS® Model StudioMaximize productivity and trust with a unified, scalable and collaborative machine learning platform.
SAS Risk Modeling frequently asked questions
What is SAS Risk Modeling?
SAS Risk Modeling is an integrated analytics platform for developing, validating, deploying and tracking credit and risk models in-house while minimizing model risk and ensuring governance.
What does SAS Risk Modeling do?
SAS Risk Modeling enables institutions to build risk models (such as credit and lending), process and manage data, and score or evaluate risk for lending products, all within a controlled and auditable environment.
What types of lending products does SAS Risk Modeling support?
SAS Risk Modeling supports virtually all lending products, including credit cards, installment loans, mortgages and commercial loans.
What are the main benefits of using SAS Risk Modeling?
- Enables data-driven risk decisions that help reduce losses and improve performance.
- Offers a scalable, in-house modeling environment that reduces dependency on external services and increases governance.
Is SAS Risk Modeling flexible? Can I combine traditional models with machine learning?
Yes, the software supports traditional statistical models, as well as machine learning and open source modeling approaches, allowing both types to coexist in the same environment.
Who typically uses SAS Risk Modeling?
Financial institutions and lenders – especially those managing credit risk, underwriting, loan originations, account management or collections – use it to build and maintain risk models internally.