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Lenders Can Improve Credit Decisions and Reduce Credit Loss

Published: June 29, 2005

SAS Credit Scoring, companies can develop predictive models that assist in evaluating the credit worthiness of customers.

SAS, a provider in business intelligence, recently announced the latest and most powerful version of SAS Credit Scoring. With SAS Credit Scoring, companies can quickly and reliably, help companies minimize business risk and provide more efficient service to their customers.

The software enables banks and financial services organizations worldwide to internally develop, validate, implement and report on credit scoring models faster, cheaper and more flexibly than any credit outsourcing alternative. SAS Enterprise Miner provides analysts with an extensive set of predictive analytic tools to support the complete scorecard development process.

The latest version of SAS Credit Scoring is supported by the SAS9 Enterprise Intelligence Platform and enhanced analytics, enabling credit scorecard development through a thin-client application that allows more flexibility for users. The solution features improved performance for interactive grouping and analyses of large datasets, resulting in faster turnaround of credit scores. SAS Credit Scoring is a modern distributable client/server solution that supports batch processing and asynchronous model training; it also includes multithreaded algorithms for faster model development. All projects are presented on the analytical server for collaborative results sharing and archiving purposes.

"SAS' philosophy of empowering customers continues with a comprehensive, in-house scorecard development solution that integrates data access and management with scorecard development and data mining for superior reporting," said Naeem Siddiqi, credit scoring strategist at SAS.

"The latest version of SAS Credit Scoring is based on SAS' many years of experience in the financial services industry and spans the entire process for credit scoring. The data models specific to financial services allow for faster implementation, reduced project risk and higher ROI. Also, financial institutions can use the knowledge gained for other customer interaction initiatives."