SAS to invest one billion dollars in developing industry-based AI solutions

Thursday, 11 May 2023 00:01

SAS to invest one billion dollars in developing industry-based AI solutions

Data analytics software and services company, SAS, announced it will invest one billion US dollars over the next three years to further develop advanced analytics solutions targeted to the unique needs of specific industries.

SAS co-founder and CEO Dr Jim Goodnight made the announcement during the SAS Innovate conference held this week in Orlando, Florida.

SAS Viya is the core platform SAS provides and will continue to provide. However, SAS chief technology officer Bryan Harris explained to iTWire "solutions will become the storyline."

"When meeting with CDOs, CTOs, CIOs, they all come back with 'solve my business problem'," he said, emphasising the value for companies in being able to buy a solution. "If some new case comes up and there isn't a solution to solve it, they can fall back to the SAS Viya platform."

In fact, vertical solutions are seen as so important to SAS that Harris says this $US 1B investment will be the basis for SAS' business for the next 50 years. Harris also explained that SAS employs many industry domain experts, and thus is able to hold meaningful discussions with business leaders about the specific problems they face in their business and industry, with SAS then able to implement these industry solutions on top of the SAS Viya platform.

This is echoed by SAS senior vice president and security intelligence Stu Bradley who told iTWire “SAS has acquired a terrific amount of domain expertise. Those domain experts deliver very specific out-of-the-box capabilities to ensure we are addressing business problems like fraud detection, and the others in a consistent way through the solution.”

Specific industries SAS will target include banking, government, insurance, health care, retail, manufacturing, energy, and more.

“Businesses face many challenges, from the threat of economic recession and stressed supply chains to workforce shortages and regulatory changes,” Goodnight said. “With insights from industry-focused analytics, resilient organizations can find opportunity in these challenges.

“Through this investment, SAS will continue to support companies using AI, machine learning and advanced analytics to fight fraud, manage risk, better serve customers and citizens, and much more. We remain steadfast in our ongoing commitment to innovation while delivering the market’s best analytics.”

The billion-dollar investment will be expended in direct research and development, industry-focused line-of-business teams, industry marketing efforts, and funding SAS data scientists, statisticians and software developers as they work with consultants, systems engineers and marketers with specific industry experience.

The investment is not surprising; SAS has long spoken of the need to democratise data analytics and put its power into the hands of more people, with more varied experiences and job roles, rather than relying on organisations having the luxury of their own data science team.

It also builds upon SAS' history of industry solutions, with some examples being:

• Last year’s economic headwinds roiled global markets, reversing post-pandemic rebounds and forging an increasingly precarious risk landscape. To help banking and insurance customers meet the challenges ahead, SAS acquired Kamakura Corp., a financial risk firm revered for its rigour, particularly in integrated balance sheet management. The acquisition is the largest in SAS history and added some of the most renowned names in quantitative risk management to SAS’ roster. It’s also accelerating advances in SAS’ suite of integrated risk solutions. Already, SAS Asset and Liability Management (ALM) has been retooled for SAS Viya, helping banks predict and mitigate the liquidity and balance sheet risks that triggered recent bank failures.
• SAS is also prioritising innovation in enterprise decisioning. Connecting siloed functions (e.g., onboarding, credit risk, fraud detection, marketing) on a unified, AI-powered architecture – and using shared data and analytics – is helping financial firms streamline operational complexity while yielding faster, more accurate decisions that boost customer experience.
• Every year, governments across the world lose huge sums due to tax evasion and avoidance. This weakens a government’s ability to provide essential services to citizens. SAS Tax Compliance helps governments protect their revenue streams by applying advanced analytics to vast amounts of tax data to automatically monitor and detect cases of non-compliance and fraud. As a result, government tax agencies can increase early identification of potential fraud, uncover emerging tax fraud schemes, accelerate audits and get old cases off the books.
• The Insurance Information Institute named 2022 the worst year in more than a decade for property and casualty (P&C) insurance. According to research by AM Best, the US P&C industry alone bore a $US 26.5 billion underwriting loss through disasters like Hurricane Ian. To stay afloat amid compounding climate risk, insurers must raise premiums to shore up liquidity, frustrating customers in an already unstable market. Quick, accurate and unbiased premium pricing is crucial to remaining solvent and competitive while promoting consumer peace of mind. SAS Dynamic Actuarial Modeling provides optimized data preparation and highly flexible modelling capabilities supported by machine learning. This helps insurers offer fair pricing in a fast, fraught market.
• SAS Health offers industry-specific applications and AI solutions across population health, operations and finance. It helps healthcare organisations deliver high-quality care that is safer and more cost-effective. Whether turning patient population data into analytic-ready cohorts or informing value-based care and payment models, SAS’ intuitive point-and-click interfaces help clinicians and business analysts advance healthcare transformation and visualize trends once hidden in their data.
• SAS also empowers clinical research that leads to new therapies and treatments. For example, about 90% of clinical trials fail to meet enrollment timelines. SAS Clinical Enrollment Simulation uses powerful analytics to inform enrollment planning, helping avoid the devastating delays that often result from missed enrollment targets.

Other examples include intelligent planning for retailers and consumer goods, electricity flow and equipment optimisation for utilities, customer intelligence for marketers, and many others.

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