AI Services

Business Challenges Retails

Mobile devices, conversational commerce, social networking and other technologies have shifted the behavior of the connected customer – and retailers and consumer goods companies need to shift accordingly. Customers can quickly research products and compare prices through multiple channels, and you must be ready to respond with relevant offers, competitive prices and the right merchandise. That means moving beyond spreadsheets, using data from every conceivable source to understand your customer’s relationship with your brand so you can influence it in real time. And then there are the challenges facing the supply side of your business. In an effort to support unified commerce, supply chain networks are becoming increasingly complex and high-speed, making them almost impossible to track or optimize.

How AI Can Help

Advances in AI for retail and consumer goods have made it possible to automate complex tasks through constant learning, enabling retailers to improve operations – and customer experiences – by breaking down departmental silos and applying omnichannel analytics to every step of the customer journey. Understanding where customers are in their journeys – and optimizing each interaction – drives longevity, loyalty and growth by turning data into action. In turn, you collect more data and learn more, so you can:
  • Replace search with conversational commerce. Natural language processing and cognitive computing have given rise to conversational computer interfaces and chatbots that enable customers to shop anywhere, anytime – giving you the opportunity to better understand customers and unify commerce.
  • Tailor efforts to specific customers.
    Uncover precise consumer needs by tapping into where and at what price customers shop across all channels and devices. Rule-based systems can’t handle the sheer number of products, customers and touch points in real time. But when driven by machine learning, your pricing, assortment and marketing are always on target down to the micromarket level.
  • Anticipate your customer’s next move.
    For every customer, AI uses thousands of pieces of text and digital data to develop a next-best action and drive recommendation engines. And you can use this insight to predict future buying behaviors, shape demand and seize opportunities to maximize margins.
  • Optimize inventory and fulfillment for online or in-store shoppers.
    Planning and adjusting the movement of merchandise can be overwhelming. AI techniques can learn and correct supply chain issues while reducing the need for human intervention. And by adding in machine-to-machine IoT analytics and RFID data streams, you can achieve real-time inventory transparency.
  • Control fraud and shrinkage.
    As the volume of digital transactions with customers and vendors continues to rise, analytic anomaly detection is the only way to keep an eye on what’s happening. Deep learning algorithms can uncover and adapt to new fraud vectors, enabling you to address money laundering, vendor procurement fraud, cashier fraud and returns abuse.
  • Power the store of the future today with analytics at the edge.
    Your physical stores have untapped potential to connect with customers. Wi-Fi foot-traffic sensors, video cameras, electronic shelf labels, and warehouse and in-aisle robotics can transform how you use every square foot. Deep learning algorithms, computer vision technology and real-time decisioning enable you to bake the art and science of retail and consumer goods into the customer experience.

Why our company?

As the proven leader in advanced analytics, only SAS bridges both merchandising and marketing data and processes across the entire retail and consumer goods enterprise. With AI capabilities embedded in our software – from our powerful analytics platform to our merchandising and customer intelligence solutions – deliver innovative analytic capabilities that allow you to better manage inventory and drive profitability. That’s why 921 retailers worldwide, including 66% of retail companies on the Fortune 500, rely on SAS to stay competitive.

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Business Challenges Health Care

The digitalization of health care data and the expectation among increasingly engaged patients for personalized and virtual care are introducing unprecedented opportunities to disrupt the way health care is delivered. Meanwhile, health care systems are overwhelmed by the flood of new, rich data sources – such as social determinants, genetic and imaging data, data from medical devices and wearables, and social media data. Health care organizations must adapt the way they use and share data to relieve pressure on health care systems and improve medical decision making to ensure greater patient satisfaction and better outcomes.

How AI Solutions for Health Care Can Help

AI capabilities – such as machine learning, computer vision, natural language processing, and forecasting and optimization – can unleash the full potential of data to improve population health and solve some of the greatest health care challenges. This necessary evolution will enable health care organizations to:

  • Improve patient outcomes. Empower physicians with more accurate diagnostics and targeted prevention capabilities.
  • Control costs. Improve the operational performance of hospitals by optimizing staffing resources and taking action to reduce the number of hospital readmissions.

Why choose us for AI in health care?

As the leader in advanced analytics, SAS has the experience and expertise to deliver cutting-edge AI solutions for health care at scale. By embedding AI capabilities in our software – from our powerful platform to AI solutions tailored to the needs of the health care industry – we provide more intelligent, automated solutions for health care that help you unlock new possibilities and solve your most complex problems.

SAS is a long-time pioneer in machine learning and natural language processing, and a quality reference for hospitals and other health care organizations. From forecasting patient interactions with every aspect of health care delivery to enabling better, more personalized care and fully optimized resources, AI solutions for health care from SAS give you The Power to Know®.

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Business Challenges Manufacturing

In manufacturing, you’re under pressure to continuously improve quality while reducing costs and increasing productivity. You also strive to right-size inventory and boost profitability while driving year-over-year cost improvements. Finding new ways to extract value from the deluge of sensor and IoT data would enable you to move from a reactive to a proactive approach to minimizing unplanned downtime, reducing scrap and rework, and developing innovative new revenue streams.

Managing the unexpected is a constant challenge. Traditional approaches – Six Sigma, line-level reporting, MES systems – are no longer sufficient for gaining insights from data to improve decision making. Finding new ways to harness the value of industrial data is essential to enabling modern manufacturers to manage today’s data volume, velocity and variety.

How AI Can Help

Advances in AI enable us to automate complicated tasks and find useful signals in data that was previously too large or complex to tackle. From quality and equipment performance, to supply chain and spare parts optimization, to service improvements and monetization of IoT data, AI techniques can unlock new insights across the spectrum of manufacturing data, enabling you to:

  • Find early indicators of potential quality issues. AI capabilities go far beyond what simple rule-based systems can do, continuously learning to automatically detect patterns in data that a human would likely never see.
  • Avoid costly scrap and rework. Use image recognition to identify flaws during the manufacturing process so you can address them promptly.
  • Identify areas for improvement. Text analytics, including natural language processing, lets you link customer sentiment, service comments and other written records to quality and production variables to identify areas for improvement.
  • Improve yield. Apply deep learning in industrial operations to optimize product composition and production techniques, combining audio, video, text and other data at efficiency levels that were previously unimaginable.

Why choose us for AI solutions?

As the leader in advanced analytics, SAS understands that a carefully designed and well-implemented analytics strategy enables manufacturers to meet their production and profitability goals more efficiently and effectively. It’s not just about getting the technology right; it’s about using data to manage complexity, reduce risk, improve margins and even create new sources of revenue.

That’s why we embedded AI capabilities in our software – from our powerful analytics platform to solutions that help manufacturers confidently detect, resolve, predict and prevent quality and reliability issues. SAS simplifies data integration from diverse systems, extracts deeper insights from data to drive productivity improvements, and can be deployed wherever and whenever you need the insights in your operations – on-machine or across the enterprise.

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Business Challenges Banks

Changing regulatory compliance requirements and shifting customer demands mean a bank’s survival hinges on its ability to glean relevant insight from all available data. In fact, the efficient and effective use of data is critical to addressing many issues today’s banks face – combating fraud and financial crimes, managing credit and regulatory risk, enhancing the customer experience and generating sufficient capital. A partnership between humans and machines – each augmenting the other – holds the most promise for successfully achieving compliance and meeting customer needs, but knowing where and how to start isn’t always easy.

How AI Can Help

From fraud to credit to risk to customer experience, artificial intelligence (AI) can enhance the speed, precision and effectiveness of human efforts, which results in a more responsive, more profitable bank. With AI capabilities from SAS, you can:

  • Turn customer experience into customer engagement. With embedded AI tools, you can stitch data together from all sources, providing an accurate and evolving view of the customer journey. You can then optimize customer journeys across all channels to maximize engagement and enable real-time decisioning.
  • Quickly identify fraudulent transactions. Use AI and machine learning techniques to identify which types of banking transactions are likely to be fraudulent. AI techniques, including adaptive machine learning and unsupervised intelligent agents, can predict fraudulent transactions in real time – and reduce false positives – based on changes and inconsistencies in customer behavior patterns. Reducing false positives boosts customer satisfaction, protects revenue and lowers costs.
  • Adopt fast, accurate credit scoring policies. When a potential customer applies for a loan or credit card, use AI and machine learning techniques to analyze alternative data sources – like utility payments, mobile phone use and text message activity – for improved loan rating accuracy to give good customers faster access to credit using real-time decisioning.

Why choose SAS?

As the leader in advanced analytics, SAS advocates applying analytics to any data that has the potential to produce insights. That’s why we embedded AI capabilities in our software – from the powerful SAS Viya to solutions tailored to the needs of the banking industry. SAS delivers open, trusted, scalable and sustainable AI capabilities that can helps banks of all sizes achieve growth, profitability and compliance. For more than 40 years, SAS has delivered consistent value to the banking industry, and more than 3,500 financial institutions around the world choose SAS to gain THE POWER TO KNOW®.

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