Enhancing data governance in financial services

In the financial sector, where compliance and regulation are of the utmost importance, innovative approaches to data governance in financial services are essential.

This evolution is driven by the need to scale securely and efficiently, leveraging advanced technologies such as generative AI and deep learning models to maintain strong security protocols while enhancing accessibility and operational efficiency, Chris Brown (pictured), public sector chief technology officer of Immuta Inc., explained.

Immuta’s Chris Brown talks to theCUBE about data governance in financial services.

“What’s unique that we’ve done at Immuta is that we’ve actually integrated into those data platforms. Now what we do is we become the policy authoring and the policy decision points,” Brown said. “We push those decisions down into those compute platforms where they become the policy enforcement point…now we’re actually giving people the true power to be able to bring in whatever business intelligence tool they want, run whatever model they want.”

Brown spoke with theCUBE’s Savannah Peterson at the AWS Financial Services Symposium, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the advancements and challenges in data security and governance in the financial services industry. (* Disclosure below.)

Innovative strategies for data governance in financial services

Navigating the complex web of regulations in the financial services industry requires a strong framework for compliance. With regulations such as GDPR, CCPA and various state-specific laws, maintaining compliance at scale is a significant challenge, according to Brown.

“It is a continual battle to be able to try to figure out how do you actually comply to all these regulations. What is good with our platform is that we take the very simple building blocks, being able to just do basic things like column masking, making sure people can’t access anything in this column,” Brown said. “Row filtering, that’s probably one of our number one use cases within financial industry…we’re able to filter all that data out for you.”

Another distinctive feature offered by Immuta is the implementation of purpose-based control, which provides clear guidelines on the intended use of the data. In addition, the integration of generative AI and large language models into data security frameworks presents both opportunities and challenges, Brown concluded.

“Where people are going to be focusing in on right now are those RAG use cases because we got to stop the hallucination. We got to make sure that things are relevant to the people,” Brown said. “Then, there’s fine-tuning … using RAG, it seems to be kind of the lightweight way, cheap way, relatively easy way for people to be able to use these models, but be able to stop a lot of the problems that occur with them.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of the AWS Financial Services Symposium:

(* Disclosure: Amazon Web Services Inc. and Immuta Inc. sponsored this segment of theCUBE. Neither AWS, Immuta nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE