As the awareness and presence of data continues rising across all sorts of businesses, banks are finding more in their vaults than physical currency. But for many organizations, bringing their systems up to speed for processing the vast quantities of transaction and interaction data at their disposal is forming a hurdle too high to overcome on their own.

FIS Global, a provider of technology for the financial services industry, recently implemented Apache Spark into its organization to help move data faster.

“Apache Spark really lifted and accelerated the entire vision of big data,” said Aaron Colcord (pictured at left), director of engineering at FIS Global.

Colcord and David Favela (pictured at right), head of data and analytics at FIS Global, spoke with Dave Vellante (@dvellante) and George Gilbert (@ggilbert41), co-hosts of theCUBE, SiliconANGLE Media’s mobile live streaming studio, during the Spark Summit East 2017 in Boston, MA. (*Disclosure below.)

Colcord and Favela shared some of their insights on how the banking industry is adapting to these challenges and where their company comes in to help, as well as how Spark assists with both higher-level abstraction focused to business cases and more granular work, as with modifying APIs to specific needs.

With FIS Global drawing in clients from a range of banking startups to existing banks looking to offer new tech services, one of the primary issues they encounter is in enabling communication and cross-usage in data stored in the differing forms and standards of each bank, Favela said.

“If you think about all the transactions that happen daily … it’s processed through a core banking system,” Favela explained, and many legacy systems simply can’t compute that data at a fast enough rate. This was one of the reason for FIS Global’s usage of Apache Spark, as well as being a driver of “a tremendous amount of transformation on the back end over the past 10 years,” according to Colcord.

“We actually implemented Apache Spark as one of our platforms to transform and help move the data faster,” Colcord stated. While finding ways to interpret data on the fly is a big part of the tasks these systems handle — even when joining multiple systems with their own standards and formatting, they’re also responsible for assembling components in ways that make sense to the end-user.

Intelligence acceleration

By creating “an intelligence layer at an analytics level,” Favela said, they can create a loop enabling better service and data handling. And the acceleration dimension of Apache Spark, along with translating away the differences of interfacing for different banks, has them building toward being able to do more calculations in real-time, particularly with customer interactions and services, Colcord noted.

Beyond those hard computational tasks, FIS Global is looking toward more abstract goals as well, most notably, “helping these institutions create a culture of being data-driven,” Favela shared. “Our clients know their customers the best, so we’re here to provide them with the tools [to serve them],” he added.

Colcord shared how FIS Global had seen the proliferation of devices and IoT as “a tsunami heading this way,” which had further motivated the company’s adoption of Spark so as to be able to handle that sort of increased volume. In a similar way, they’re looking to ease the heavy work eating up banks’ time with data handling so they can begin thinking about introducing new services building from that.

Looking ahead, in spite of the current moves toward business deregulation, Favela doesn’t anticipate the complexity of bank standards compliance, and the services FIS provides in that realm, to be going away anytime soon.

Watch the complete video interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of the Spark Summit East 2017 Boston. (*Disclosure: TheCUBE is a media partner at the conference. Neither Databricks nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo by SiliconANGLE