To add fuel to the artificial intelligence fire, data ought to take center stage, and this is why AI data integration has become top of mind across different industries. 

To incorporate AI capabilities into its data estate, the Bank of New York Mellon Corp. teamed up with ThoughtSpot Inc. and Snowflake Inc., according to Mark D’Costa (pictured, right), head of data innovation and commercialization at BNY Mellon.

ThoughtSpot’s Cindi Howson and BNY Mellon’s Mark D’Costa talk to theCUBE about the importance of AI data integration in banking.

“The LLMs and generative AI have just been an amazing kind of jolt to the organization in the industry,” D’Costa said. “The focus on that new technology and the prospect that it has, has then just turbocharged the focus on data. What you couldn’t do in any way on-prem now becomes possible once you’ve broken through into the cloud with both ThoughtSpot and Snowflake.”

D’Costa and Cindi Howson (left), chief data strategy officer of ThoughtSpot Inc., spoke with theCUBE’s Rebecca Knight and Dave Vellante at Data Cloud Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how BNY Mellon has set the AI data integration ball rolling in banking with the help of ThoughtSpot and Snowflake. (* Disclosure below.)

How a data strategy fits into the AI data integration picture

Having the right data strategy plays an instrumental role in triggering AI and gen AI innovations in financial services. For instance, gen AI helps with data observability and crowdsourcing business definitions, making AI data integration seamless as showcased by BNY Mellon, according to Howson. 

“It’s about going from that defensive, protect the data, to offensive, make that data actionable and get the insights,” she stated. “If I apply for a mortgage at BNY, they’re using traditional AI. The gen AI is what is really important in revitalizing this industry that has taken it now to a boardroom conversation. Without a data strategy, you cannot have an AI strategy. With BNY Mellon investing in products and platforms like Snowflake, that puts them in a better position to leverage generative AI.” 

AI data integration requires organizational change, such as shifting mindsets about data. As a result, data should be put in the hands of business users or at the point of impact, and BNY Mellon is able to make this a reality thanks to its collaboration with Snowflake and ThoughtSpot, D’Costa pointed out. 

“As this whole focus on generative AI and data transformation is taking place, the organization’s also going through an organizational transformation,” he noted. “As we start to shift the data gravity to the cloud, we’re trying to offer ThoughtSpot as a tenanted service. What we have been doing with Snowflake is creating a very tenanted structure that was governed to enable all these different lines of business that came together at the right time.”

The cloud is emerging as an ideal stepping stone toward BNY Mellon’s objective of democratizing data and providing wider access. The cloud is also materializing as a perfect fit in the bank’s AI data integration journey, according to D’Costa. 

“A lot of why we’ve gotten through to the cloud has also been our clients,” he said. “They want to start to receive their data in a connected form. We’re early on this journey, but we already are partnering with clients in order to work through Snowflake sharing in order to get data just showing up on their doorstep as opposed to shuttling it across and having them reconstituted in their environment.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of Data Cloud Summit: 

(* Disclosure: ThoughtSpot Inc. and the Bank of New York Mellon Corp. sponsored this segment of theCUBE. Neither ThoughtSpot, BNY Mellon nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE