List of SAS Model Manager Customers
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Since 2010, our global team of researchers has been studying SAS Model Manager 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 Model Manager 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 Model Manager for Analytics and BI include: Georgia-Pacific, a United States based Manufacturing organisation with 30000 employees and revenues of $7.50 billion, Bank Leumi, a Israel based Banking and Financial Services organisation with 7833 employees and revenues of $6.67 billion, S-Bank, a Finland based Professional Services organisation with 990 employees and revenues of $55.0 million and many others.
Contact us if you need a completed and verified list of companies using SAS Model Manager, 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 Model Manager 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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Bank Leumi | Banking and Financial Services | 7833 | $6.7B | Israel | SAS Institute | SAS Model Manager | Analytics and BI | 2017 | n/a |
In 2017, Bank Leumi implemented SAS Model Manager to strengthen governance of credit-risk models within its finance and risk function in Israel. The deployment was part of the bank's wider use of SAS products and aligned with its Analytics and BI tooling for model lifecycle control and evidence consolidation.
The SAS Model Manager implementation included model inventory and documentation capabilities, automated validation workflows, and continuous monitoring pipelines for model performance and stability. Configuration emphasized repeatable validation procedures, model version control, and scheduled monitoring to detect performance drift and support reproducible validation artifacts.
Operational coverage focused on credit-risk modeling across the finance and risk departments in Israel, centralizing model metadata, validation outputs, and regulatory artifacts into a single managed environment. This consolidation provided a unified source for validation evidence and documentation needed for supervisory reporting.
Governance and process changes formalized documentation standards, embedded validation checkpoints in approval workflows, and established ongoing monitoring processes to reduce model risk. The deployment improved model documentation, automated validation, and ongoing monitoring to reduce model risk and support regulatory reporting demands.
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Georgia-Pacific | Manufacturing | 30000 | $7.5B | United States | SAS Institute | SAS Model Manager | Analytics and BI | 2020 | n/a |
In 2020, Georgia-Pacific implemented SAS Model Manager as part of a SAS Viya on AWS deployment to manage, deploy and monitor large numbers of machine-learning models that optimize manufacturing and supply-chain processes. The implementation is categorized under Analytics and BI, and SAS Model Manager serves as the central model lifecycle platform supporting model registration, deployment orchestration and runtime monitoring across operational pipelines.
The deployment architecture leveraged SAS Viya on AWS, with SAS Model Manager providing a centralized model repository, model versioning and automated monitoring capabilities. The environment was configured to handle IoT-driven predictive maintenance workflows, ingesting sensor and equipment telemetry for online scoring and batch inference, and to operationalize models for supply-chain optimization and production scheduling.
Operational coverage focused on US manufacturing sites and supply-chain functions, with business functions including plant operations, maintenance engineering and supply-chain analytics using the SAS Model Manager. Governance practices were enacted for model monitoring and post-deployment validation, including workflows for detecting model drift and triggering retraining or remediation. The program delivered measurable reductions in unplanned downtime and improvements in equipment efficiency through IoT-driven predictive maintenance and continuous model monitoring.
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S-Bank | Professional Services | 990 | $55M | Finland | SAS Institute | SAS Model Manager | Analytics and BI | 2021 | n/a |
In 2021, S-Bank implemented SAS Model Manager and SAS Viya to automate credit scoring and to improve loan processing and customer-service analytics within its retail banking operations in Finland. The work is categorized in Analytics and BI and positioned SAS Model Manager as the model governance and deployment layer of the solution.
SAS Model Manager was configured to support model lifecycle management functions such as model registration, versioning, validation, and automated promotion into production scoring pipelines. The implementation included configuration of credit scoring workflows and scoring orchestration to feed loan decision processes and customer-service analytics use cases.
The Finland deployment standardized model lifecycle processes across analytics teams and business stakeholders, aligning model outputs with loan decision workflows and customer-service analytics pipelines. Operational coverage focused on retail banking credit decisioning and customer engagement analytics in S-Bank’s core markets.
Governance changes centered on formalizing model stewardship, approval gates, and reproducible validation steps managed through SAS Model Manager, improving alignment between analytics teams and business stakeholders. The stated outcomes were faster loan decisions and standardized model lifecycle processes, achieved through the combined use of SAS Viya and SAS Model Manager.
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