List of SAS/ETS Customers
Cary, 27513-2414, NC,
United States
Since 2010, our global team of researchers has been studying SAS/ETS customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased SAS/ETS for Analytics and BI from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using SAS/ETS for Analytics and BI include: Stanford University, a United States based Education organisation with 18369 employees and revenues of $8.90 billion, University of Utah, a United States based Education organisation with 46000 employees and revenues of $7.26 billion, Wescom Credit Union, a United States based Banking and Financial Services organisation with 924 employees and revenues of $165.0 million and many others.
Contact us if you need a completed and verified list of companies using SAS/ETS, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The SAS/ETS customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Stanford University | Education | 18369 | $8.9B | United States | SAS Institute | SAS/ETS | Analytics and BI | 2025 | n/a |
In 2025, Stanford University provisioned SAS/ETS as part of its campus SAS licensing to support teaching and academic research in econometrics and time-series forecasting. SAS/ETS is listed under Analytics and BI and is made available to students and researchers across campus systems in the United States for coursework and research projects, supporting education and research functions across the university.
The deployment is governed through Stanford's campus software licensing program, with access scoped to academic entitlements and campus-hosted systems rather than enterprise production use. SAS/ETS delivers econometric modeling and time-series forecasting capabilities typical of the Analytics and BI category, enabling hands on forecasting, model estimation, and validation workflows for coursework and researcher-led projects.
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University of Utah | Education | 46000 | $7.3B | United States | SAS Institute | SAS/ETS | Analytics and BI | 2025 | n/a |
In 2025, the University of Utah provisioned SAS/ETS as part of its campus SAS offering, cataloged under Analytics and BI. The deployment is positioned for instructional and institutional research use across the United States, and the availability is documented in the university software licensing pages that make the application accessible to faculty and students.
SAS/ETS is published by the university for econometrics and time-series analysis, reflecting explicit functional emphasis on model specification, estimation, and forecasting within academic coursework and research projects. The University of Utah uses SAS/ETS capabilities to support statistical analysis and time-series workflows consistent with Analytics and BI tooling in higher education.
Operationally, access to SAS/ETS is governed through the campus software licensing program, which centrally catalogs and distributes the campus SAS offering to eligible faculty and students across academic departments involved in economics, statistics, and institutional research. The implementation scope is education and research within the United States, with provisioning handled via institutional license and campus distribution channels documented on the university site.
Governance relies on university licensing controls that define entitlement and access for instructional courses and institutional research, and SAS/ETS is embedded into classroom instruction and research toolchains to support faculty and student analytics workflows.
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Wescom Credit Union | Banking and Financial Services | 924 | $165M | United States | SAS Institute | SAS/ETS | Analytics and BI | 2008 | n/a |
In 2008 Wescom Credit Union deployed SAS/ETS as part of an Analytics and BI initiative to operationalize econometric and time‑series forecasting for credit-risk and loan-loss forecasting in California, United States. SAS/ETS was used to support predictive modeling work that directly informed finance and lending decision processes at the credit union.
The implementation emphasized econometric estimation and time-series forecasting capabilities, enabling structured forecasting workflows and credit-scoring analytics. The SAS case study cited SAS Forecast Server and credit-scoring solutions, and SAS/ETS usage is inferred because the engagement relied on econometric and time-series forecasting methods described in the project documentation.
Operational coverage focused on the finance organization and credit-risk functions responsible for loan-loss provisioning and lending decisions, with forecasts feeding underwriting and charge-off assessment workflows. The deployment centralized forecasting models and scoring routines for use by credit analysts and finance teams across Wescom Credit Union locations in California, United States.
Governance changes included embedding model-driven forecasts into lending decision workflows and establishing repeatable scoring and forecast refresh processes to support ongoing credit-risk monitoring. Model documentation and routine forecasting schedules were part of the operational control framework to ensure consistency of inputs to lending and provisioning processes.
The engagement produced large improvements in lending decision accuracy and multimillion-dollar reductions in charge-offs as reported in the SAS case study, demonstrating the practical impact of SAS/ETS driven econometric and time-series forecasting on credit-risk and loan-loss forecasting outcomes.
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