SAS® Credit Scoring
A faster, cheaper, more flexible solution than any outsourcing alternative.
Quickly develop, validate, deploy and track credit scorecards in house – while minimizing model risk and improving governance. We've combined award-winning data management, data mining and reporting capabilities in a powerful credit scoring solution that is faster, cheaper and more flexible than any outsourcing alternative.
Benefits
Make well-informed credit decisions.
Reduce credit losses and boost your overall business performance by making better, data-driven credit decisions on both the origination and servicing sides of your business. SAS Credit scoring enables you to perform application and behavior scoring for virtually all lending products – including commercial loans, cards, installment loans and mortgages.
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 scorecards. You can work collaboratively, sharing variables, filters and other parameters to maintain corporate IP and reduce your governance risk. In addition, you have the flexibility to reuse existing SAS code.
Easy data access and management.
Access, transform, standardize and cleanse all relevant data to create a 360-degree view of the customer. A banking-specific data model lets you build a robust, easy-to-access data mart that ensures consistency, powered by integrated data extraction, householding and deduplication, mapping and loading capabilities.
Fast in-house scorecard development.
Develop, validate and implement unlimited application and behavioral scorecards in-house with our end-to-end, integrated solution. You'll get models and scorecards 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.
Screenshots
Recommended Resources
Learn strategies for designing an effective infrastructure for credit risk model development.
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