R34DY: Connecting the Building Blocks for Core Banking Systems

Ever more intelligent chatbots and roboadvisors, seamless remote loan applications and a sophisticated architecture to serve instant payments. These are the tech features most often discussed by the public when it comes to the latest banking tech. You will hear a lot less, in the mainstream media, at least, about the reinvention of core banking systems, the back-end processes that move banking transactions around the various branches of a bank.

We are talking about a very hot topic, though. Founder and CEO of R34DY Zrt. Márk Hetényi tells the Budapest Business Journal that it all started when Oracle charged it with implementing its core banking solution, Flexcube, a finance service and banking management app that helps businesses build multiple portfolios of products.

“We saw that small- and mid-sized banks and fintech companies built their product and sales competencies, but they lacked the deep business expertise necessary for a Flexcube implementation,” he explains.

“Our combined expertise in banking, IT and business came in handy for customers so that they could get the most out of Flexcube,” Hetényi says. Clientele also showed interest in benefiting from the system’s functions as a service. That’s how R34DY’s own Core-Banking-as-a-Service (CBaaS) solution came about.

The origin of the market uptake lies in the complexity of banking architecture. As Hetényi notes, lenders tended to put all the complex functionalities into their core banking system, but guard access to it very closely. As a result, it became an oversized hornet’s nest that nobody wants to kick; a paradigm shift has been long overdue.

New generational developments have triggered an evolution in which a black box set-up is replaced with a sandbox approach.

Lego Flexibility

“Now we are experiencing a modular structure instead of a single massive one, which provides more flexibility. The system can also be extended more easily,” the expert says. “You can have a thousand Lego bricks, and you will need to learn how to put them together,” he says. But if these individual services, some of which are pretty small, are connected well, a fantastic package will emerge.

In the IT architecture, an orchestration of layers is created that aims to ensure those Lego pieces stick together. The complexity has not disappeared but lives on in a different, more useable form. At the same time, standardizing services is critical as it paves the way for going to market much faster, Hetényi adds.

His company’s CBaaS solution offers flexibility on another front: it is available in on-premises, hybrid and cloud forms. The cloud enables customers to build better scalable systems that can be operated more efficiently.

Furthermore, R34DY provides the option of one-off or continuous services. The former typically includes more extensive projects such as migrations or system implementations, whereas the latter concerns day-to-day activities, reporting needs or preparing business specifications.

Small- and mid-sized banks can, therefore, use Flexcube without necessarily having to build core system competencies. As the R34DY motto goes, “Core banking does not need to be your core competency.”

The company aims to place less functionality in core systems and instead focuses on orchestration and middleware layers. Again, this is beneficial for small- and mid-sized banks in particular, as they don’t have the resources or expertise to develop and maintain their own core banking systems. Instead, CBaaS allows them to adopt cutting-edge banking technologies without making substantial investments, while updates and maintenance come from the provider.

AI Potential

AI helps integrate third-party services and thus serve various use cases. Although Hetényi was initially skeptical about artificial intelligence, he now sees enormous potential.

“After the probabilistic world of generative AI, I became a profound believer in RAG models and their potential, and now I am genuinely excited by the world of agents and AI chains,” he notes. For the uninitiated, RAG, or retrieval-augmented generation, is the process of optimizing the output of a large language model so it references an authoritative knowledge base outside of its training data sources before generating a response, as Amazon Web Services explains it.

“I really enjoy breaking down a process, whether business, cognitive, decision or other, into sub-parts with the team and finding the right AI model for the smaller sub-parts, and slowly but surely (or quickly but surely!), we are moving towards solutions,” Hetényi says.

The evolution of R34DY’s solution is expected to lead to a move beyond the current CBaaS model and build an integration platform through which complete pre-integrated use cases (such as know your customer requirements, anti-money laundering, or fraud management) will be made available to banking partners, the expert adds.

R34DY’s goal is to eventually turn its solution platform into an orchestration service provider by connecting various third-party service providers.

“We plan to develop a mechanism through which customers can build their services in a plug-and-play manner using the Lego elements available on our platform, either on their own or by using R34DY competencies,” Hetényi adds.

This article was first published in the Budapest Business Journal print issue of March 22, 2024.