The traditional roles of financial institutions are shifting. Beyond just holding money and disbursing loans, today’s banks have to accommodate new functions, such as creating digitized customer experiences driven by hybrid cloud.

One of the prominent themes at this week’s SAS Explore event revolves around SAS Institute Inc.’s billion-dollar investment in advanced analytics solutions. With the expanded threat surface created by digitization, how can these solutions help financial services providers mitigate fraudulent activities while carving out new avenues for profitability?

“Something that we’ve been speaking to our customers about all year is real-time balance sheet management [and] asset liability management,” said Jack Thompson (pictured, right), head of U.S. financial services at SAS. “These things are emerging. As the artificial intelligence hype cycle extends and as we see the reality of what AI can bring to the table, it’s also important that you have governance, scale and control. And that’s what SAS is bringing to the table.”

Thompson and Paresh Patel (left), senior principal data platform engineer at Discover Financial Services, spoke with theCUBE industry analysts Dave Vellante and John Furrier at SAS Explore, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They shared insights into large-scale data, AI in financial services and SAS’ role in addressing the complex resulting challenges. (* Disclosure below.)

The big investment bet to transform industries

From a financial services angle, SAS sees value in making the aforementioned investment to solve complex problems, including financial fraud mitigation and risk management. And, as AI’s capabilities evolve, maintaining governance, scalability and control become paramount.

There’s also the data piece. Financial services companies often generate, store and move high data volumes across different infrastructures. SAS is adept at handling vast volumes of data efficiently, emphasizing the importance of scalability for financial institutions, according to Patel.

“Big data, the volumes of data — for financials, that’s a very common theme,” he explained. “We do not deal with gigabytes; we deal with multiple gigabytes. Also, SAS is the tool that … easily scales in the processing of the data — whether that is megabytes of data, gigabytes of data or hundreds of gigabytes of data.”

As SAS blueprints its investment’s rationing through its enterprise decisioning framework, financial services will receive a considerable chunk, according to Thompson. In addition to fraud prevention, the company’s investment will also focus on asset and liability management innovations.

“From a SAS perspective, 44% of our $3.2 billion in revenue is coming from financial services,” Thompson stated. “We’ve just started to release our enterprise decisioning framework. Fraud is a huge part of that. We’re releasing new versions of our ALM and fraud solutions at the end of the year. When it comes to fraud and enterprise risk management, those are at the top of the list so far as our solutions.”

On the data democratization topic, the goal is to avoid the pitfall of creating data swamps and ensuring that data remains accessible, scalable and secure, according to Patel. There’s also a need for a well-defined strategy when transitioning to the cloud, with a thoughtful approach balancing cost considerations, technical requirements and user experience.

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of SAS Explore:

(* Disclosure: TheCUBE is a paid media partner for the SAS Explore event. Neither SAS Institute Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE