SAS® Risk Modeling
A faster, cheaper, more flexible risk modeling solution than any outsourcing alternative.
Quickly develop, validate, deploy and track risk models in house – while minimizing model risk and improving model governance.
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.
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.
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.
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.
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.
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
Award-winning data management, data mining, machine learning and reporting capabilities in a low-risk, integrated risk modeling solution.
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.
Explore More on SAS® Risk Modeling & Beyond
Article
Credit Risk Decisioning in the Age of Digitalisation
Read about the internal and external digitalisation challenges when it comes to credit risk decisioning processes and how they can be overcome.
White Paper
Six Keys to Credit Risk Modeling for the Digital Age
Learn about the emerging role of machine learning and alternative data in credit decision making.
Insights
Risk Management Insights
Learn about the latest news, views and best practices in risk management from the brightest minds in the business.
Related Offerings
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