Data doesn't change your business. Decisions do.
Pricing a product or policy. Catching machine defects before they affect a manufacturing line. Identifying fraud. Validating a claim. Making a credit decision. Determining the next best action to take at any point along a customer's journey. Companies must make thousands of decisions like this every day.
Using analytics to drive these decisions is critical in order to ensure the best decisions are made every time. SAS delivers powerful analytics and decisioning capabilities to efficiently augment and automate your decision making at scale.
DID YOU KNOW?
Decisioning is rapidly becoming a must-have for most companies.
major new business systems that will use real-time context data to improve decisions by 2022
share of decisions made during a customer engagement that will be completed by smart machines by 2030
share of analytics budget used by breakaway companies to embed analytics in core workflows and decision-making processes
What People Are Saying
SAS is a Leader in the 2020 Gartner Magic Quadrant for Data Science & Machine Learning Platforms.
Read the report
SAS can help organizations in virtually every industry benefit from decisioning as they grapple with digital transformation, changing competitive landscapes and rising customer expectations.
Banks all over the world use SAS to make analytically driven decisions – from providing personalized, trusted customer experiences, to meeting risk and compliance mandates, to preventing fraud – in the midst of rapid changes due to digitalization, fintech, open banking, faster payments, data privacy, regulatory compliance and more.
SAS helps retailers today with diverse decisioning opportunities – such as meeting merchandising demands for specific locations, improving the supply chain with near-real time inventory balancing, guiding customers on a path to purchase through personalized digital interactions, and detecting and preventing fraud quickly to minimize margin losses.
Decisioning capabilities from SAS offer a wealth of possibilities for insurance companies – from striving to meet compliance requirements such as IFRS 17, to detecting and preventing claims or underwriting fraud, to using IoT data and AI to generate real-time pricing, to offering health and well-being services.
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