For SAS, it’s all about bringing trustworthy value to AI

For Gavin Day, Chief Operating Officer (COO) and Executive Vice President at SAS, companies that have a measured approach to picking very specific business problems that they want to solve and using AI for that, are the ones that are getting the AI ROI.

When it comes to data and AI, SAS continues to be a leader in enabling organizations to transform data into trusted decisions. As the vendor turns 50 this year, the past half century has been filled with innovations in data, from analytics to management as the volume of data generated continues to increase exponentially.

With AI use cases dictating data management these days, organizations need to ensure they have the right data processes in place. In the Asia Pacific region, SAS works with a variety of customers and industries in their data journey. While banks and financial services are primarily the vendor’s key customers, the increasing use of AI has seen the need for SAS solutions in other industries as well.

In a conversation with CRN Asia, Gavin Day, the Chief Operating Officer (COO) and Executive Vice President at SAS explained that while the vendor does have a strong presence in the financial services industry, there are also customers in the public sector, life sciences and healthcare.

“If we look at our core markets, there's a priority in every geography for us. We make selections in specific geographies based on capabilities, based on our customers around telco, retail and such. So, the financial services is a big market for us, but the others are equally as important,” he said.

Looking at the Asia Pacific market, Day shared that there is a strong focus this year in the region, especially since 55% of the vendor’s revenue comes from outside the US. As such, the vendor will continue to focus on its presence in Australia, New Zealand, the Philippines, Malaysia, Thailand, Japan and Singapore.

“These are all markets where we have established presence and will continue to grow. So, we have customers all over the world and it remains an area of innovation. I think the financial services industry as a whole, is always leading-edge companies. A lot of the banks that we work with, are trying to decide if they're a bank or if they're a software company, because sometimes they have more engineers than we do. So, working with them on mainstream adoption and getting back to the foundation of what got us here as an industry, which is data analytics AI. We love to focus on the end part of generative AI and it's important, but without the foundation, then our customers aren't going to be successful,” Day said.

Trustworthy AI

Interestingly, while AI innovation and adoption continue to increase, the situation may not be the same in the banking industry. According to new banking insights from SAS’ Data and AI Impact Report: The Trust Imperative, with research insights by IDC, even as banks accelerate AI investment faster than other sectors, most are deploying AI without the oversight and infrastructure needed to earn that trust.

Specifically, the study revealed that only 11% of banks have achieved both high internal confidence in AI and AI systems that are demonstrably trustworthy. Also, nearly half (47%) of banks fall into what IDC calls the “trust dilemma” – either underusing reliable AI because they don’t sufficiently trust it or over relying on AI systems that haven’t been adequately validated.

“In this era of AI, we're seeing that our customers want to use AI in a trustworthy way in order to build trust with their customers. And that is absolutely an area that we continue to focus on,” Day explained.

Day pointed out that there's a lot of experimentation going on when it comes to AI. However, as businesses spend a tremendous amount of money on AI, the results that they're getting from it at an enterprise level is still disappointing in a lot of areas.

“AI for personal productivity is getting much better, but enterprise scale and class benefits, they're not there yet. And it's one of the reasons I think we've taken a very cautious and measured approach with what we wanted to bring to market. One of the things we say internally is just because you can use technology for something doesn't mean you should. So, we hope that our customers continue to focus on trust as it relates to generative AI and then I think we'll get into some scalable benefits,” he added.

AI ROI

On the topic of benefits, Day also pointed out that there continues to be pressure on the ROI that businesses are getting. He feels that the companies that SAS is dealing with, which have a measured approach to picking very specific business problems that they want to solve and using AI for that, are the ones that are getting the ROI.

“We said this with neural networks. We said it with the chatbots of a couple of years ago. It's the same with AI and generative AI. Companies have to pick up a problem that's core to their business and not something that's just an experiment. The second part of that is designing the project and the use cases for generative AI that they can responsibly get into production,” he explained.

“It's easy to put a prototype in place, right? It's easy to just create a model, but can you, use it with the technology, the people that you have, get that over the wall and move it into production and have it governed and have it measured and understood from an explainability perspective? What data did I use? What decisions am I making? That's where I think the companies that are approaching that holistically are getting some of the ROI versus the experiments, which you're not going to ever move those into production,” he added.

A real example in the region is DB Insurance. Specifically, DB Insurance partnered with SAS to develop Korea's first AI-powered fraud detection network, enabling investigators to identify invisible fraud connections as visible patterns on their dashboards. The DB T-System, built on SAS Viya, unified operational and informational data from across the business, bringing decades of policy, claims and customer information together on a single platform.

By continuously mapping relationships across DB Insurance's entire customer base, the system could now track how and where accidents occurred, which hospitals patients visited, how long they stayed, and which repair shops they used. For the first time, investigators could see an entire ecosystem of behavior – and how seemingly unrelated events were linked together, as well as how people and organizations overlapped. Patterns of deceit emerged from the noise.

“And so being able to measure not only the ability to detect that fraud but then provide the value-added benefit it has for the rest of their customer base is a great success story of AI ROI. It's a great local regional story where they're very specific about the use case that they wanted to solve, got the ROI from that, and then it had this broader customer experience impact for the rest of their customers,” Day said.

50 years of innovation

As SAS approaches its 50th anniversary, Day also shared that it’s a rather interesting scenario as the vendor believes that they pioneered the data statistical analysis category nearly half a century ago.

“The market size is so big, everybody wants to be a part of it. So, for us, we focus on what the value is that we add. And so we try to be really clear about our mission, our vision, and how we support our customers. That's been a very clear priority for us. When we think about competitors, we'll run into competitors that are independent software providers on the tool and platform side, to as we get into some of our package solutions, we'll hit another set of competitors,” said Day.

“We always find it when we win, and we've got lengthy relationships with customers. It's because they trusted SAS. And they trust not only our software, but our domain experts and our people. And so, I think it's even more important in this era of AI, where sometimes relationships can feel synthetic. And we're going to continue to double down on the relationship that our people have with our customers,” he concluded.