As established banks enhance their data capabilities and new market entrants seek cost-effective analytics innovation, SAS claims to have something for everyone and an answer to threats from the upstart fintech community.
One might be forgiven for thinking that the storied analytics company's offerings are less attractive to some sector firms as other vendors pitch similar offerings at a lower price. But SAS founder Jim Goodnight is keen to stress that his company is perfectly able to serve banks large and small, old and new.
With the unfazed demeanor of someone who has seen countless waves of innovation over the years yet has remained sufficiently ahead of the game to remain relevant, Goodnight sticks to his guns despite fierce competition in the analytics space. At the SAS flagship annual customer event in Denver, he said:
Because we’ve been around for 40 years, people think our software is old, but you’re not going to be around for 40 years if you don’t improve your software. We improve it year after year and spend 25 percent of our total revenue on R&D, which is way more than any other major software company.
A perception people have is that they knew SAS when they were in college, so therefore it must be old. But right now, as far as advanced analytics, data mining, machine learning is concerned, we’ve got some of the most advanced software in the world.
According to Goodnight, his company is still "years ahead of anybody else" in the data intelligence arena.
We do neural networks and deep learning in parallel, so hundreds of times faster than some processor on a single machine. And we have failovers: when a server goes down, we automatically bring up another one to take its place.
He adds that there is no match in the market for what SAS does, particularly when it comes to the "completeness" of its offering.
No other platform has got this total analytical lifecycle from data ingestion, all the way through model deployment without any re-coding. It doesn’t exist anywhere.
But clients, particularly new, leaner financial services players, want an analytics provider that is responsive, in tune with their needs and preferably without lock-ins and hefty fees. Goodnight says that SAS can tick most of these boxes, but is upfront about the cost aspect.
All I can say is that it costs a lot to train people to make up for the fact that a software might not have all the features or all the capabilities. Then before you’ve even created a model, you’ve got to use some other package to try to get the data ready to be analyzed; and when that is finished, you’ve got to have a program that can put your model into production, so that it can be operationalized - none of that is free.
To better serve its financial services customers Goodnight's approach is to create and enhance focused divisions, a key example being risk - an area in which SAS continues to invest heavily. He says:
All of the bigger banks use SAS to do risk management, so we do an awful lot of work on that. They don’t use our own specially tailored risk management software because they prefer to do their own, but they bring our expertise in for many other things, especially for anti-money laundering.
And even there, we’ve moved that into a massively parallel environment, so that we can feed data in extremely rapidly to run anti-money laundering tasks. We do the same thing with credit and debit card fraud as well as online fraud. We’re involved in the whole chain.
According to Goodnight, the risk group at SAS has been getting a considerable amount of traction, with 25-30 percent growth yearly and future prospects are promising:
I think we will certainly become a risk standard, especially our risk model management platform. Even if companies want to do their own risk computations, we’re receiving a lot of interest in our model computational platform, which manages and keeps track of what models, variables and features that have been tried and how well they perform.
No fintechs, thanks
Contrary to what most vendors in the financial services space are doing, SAS is not interested in setting up the so-called fintech ecosystems to aggregate functionality to its products. The closest the firm has got to that kind of set-up is a partnership with Jack Henry & Associates, a payment processing software and services provider, for a cloud-based financial crimes predictive analytics offering.
According to Goodnight, SAS is open to partnerships, but fintechs are not necessarily keen to work with his company. He said:
Many of the fintech organizations want to do their own thing, so they can sell it and keep all the money. They want all the value for themselves, so for most of them, [partnering with SAS] is not interesting.
Banks want to tap into the fintech world partly for technology innovation and that includes analytics capability, but user organizations often find it problematic and costly to handle their own ecosystems. For Goodnight, that is not an unfamiliar scenario.
Some [banks] have tried [to engage with fintechs] and they’ve come back to us. We’ve been around this long because we keep improving but we also don’t rest on our laurels.
Part of the job of navigating in the current business landscape also involves ignoring a lot of the noise around any new entrants possibly becoming a threat to SAS. On that topic, Goodnight is also consistently straightforward:
If they become a threat, we’ll go after them. That’s the way it works.
Jim Goodnight is and always has been good speaking value. As the founder and majority owner of SAS, he has the luxury of being able to chart the course of the company, free of pesky regulatory constraints or the oversight of financial analysts, keen to boost a stock price. And let's not forget that while he once dallied with the idea of going public, it didn't sit comfortably with him.
Even so, and despite its storied history, SAS faces existential threats albeit the sentiment among knowledgeable analysts is that the hype around AI and ML is running out of control and due for a much-needed reset. That works in SAS favor, especially since the company has a long history of managing the analysis of risk and fraud prevention work on which banks have come to rely. Whether the fintechs offer credible alternatives is another matter but the fact banks are investing directly in those nascent solutions should be a warning sign.
But - don't bet against SAS. They know this stuff like no other analytics vendor and are used to fielding deeply experienced PhDs that have financial services industry smarts.