Perpetually driven by one technology or another, enterprise transformation is a never-ending discussion. With companies still in their cloud transformation journeys, implementing cutting-edge breakthroughs, such as multicloud and edge computing, a new transformation driver is here.

That driver is artificial intelligence, and it’s already poised to reshape the banking and finance sector, overhauling the concept of end-customer service delivery and new product development.

“I love the partnership between us at Mambu,” said Charith Mendis (pictured, right), head of the worldwide banking industry at Amazon Web Services Inc. “It’s been a longstanding partnership and [it’s] transforming the banking industry from a core banking and composable banking point of view. Together, what we’ve been able to do is not just transform what’s happening in the core bank, but how you actually change customer experience and how you use machine learning around the core bank to transform how banking is delivered around the world, whether that’s in Europe, the U.S. or Latin America.”

Mendis and Omar Paul (left), senior vice president of product and engineering at Mambu B.V., spoke with theCUBE industry analyst John Furrier, during a CUBE Conversation from SiliconANGLE Media’s livestreaming studio in Palo Alto. They discussed the financial services industry as it navigates the evolving AI landscape, with partnerships such as the one between Mambu and AWS set to play a crucial role in shaping the future. (* Disclosure below.)

AI’s arrival in banking and the challenges being navigated

Mambu is a cloud-based banking platform serving over 260 corporate customers across 65 countries, spanning neobanks, fintech solutions providers and traditional banking institutions. The company operates a cloud-based banking platform that serves over 75 million end users worldwide, according to Paul.

One key challenge that Mambu deals with, as part of the AI puzzle, is data quality and reliability. Data residency laws pose another challenge, particularly for a platform such as Mambu, which has customers in disparate countries, Paul added.

“The quality and reliability of the data, as well as the semantics you can drive from it and who owns it, is vital to what you can do with it,” he explained. “Mambu is the transaction source of record, so if somebody makes a deposit or gets a loan and an interest rate calculation has to occur, we have that transaction information. The challenges we tend to have with AI are … the use of data and how you can project it forward. Some of it is personally identifiable information, so you have to watch what insight you can derive from it and who sees it.”

The need to comply with regional regulations, such as the EU Sovereign Cloud, highlights the complexity of managing data across borders. Additionally, the ethical considerations of using AI in decision-making processes, especially in areas such as automated credit decisions and risk profiling, emphasize the importance of responsible AI practices, according to Paul.

Enabling AI for product enhancement

To fully harness the next wave of transformation and optimize output and efficiency, financial institutions are looking past core banking operations and exploring value areas such as enhancing customer experiences through machine learning. The ability to leverage the cloud for speed and agility is also a key factor.

“I think the use of generative AI and even traditional AI to drive innovation in that industry is really accelerating,” Mendis said. “We’re early on the journey, but we see so many interesting use cases in terms of everything from customer service and [maintaining a] human in the loop to removing the friction in that customer service point of view. Also, how do you improve the efficiency of the knowledge worker? Whether that’s doing document processing in the mortgage business or an investment advisor, how do you drive that?”

The cloud-native nature of Mambu’s platform offers advantages in terms of regional coverage, enabling financial institutions to meet specific requirements related to network, latency and compliance. Additionally, the ease of using AWS services facilitates rapid innovation and agility, allowing Mambu to offer customized solutions to its diverse customer base.

Mambu has a tiered approach to AI integration and implementation. The first area is internal productivity, where it harnesses tools, such as AWS Lambda functions, to streamline internal processes and enhance productivity. On the customer interaction side, AI is employed in areas ranging from knowledge bases to responding to requests and proposals. Mambu leverages generative AI to identify patterns in responses, enabling quicker and more accurate responses to customer queries.

“The third bit is the use of AI in data insights to help customers make decisions,” Paul said. “If I’ve got a customer who has branches in five countries in the EU, data laws allow me to use that. Now, if I went from the EU to the Middle East, I can’t do that. But within the EU, buying patterns may be different because we are the transaction source of record. I can give the customer predictive information that says, ‘Customers in France tend to think about it this way.'”

Here’s theCUBE’s complete video interview with Mendis and Paul:

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

Photo: SiliconANGLE