GCC Banks face AI gap: core systems need overhaul

SPEAKER_1 (0:00)

It's the Morning Drive from Mira Business FM in Dubai. Wherever you're joining us from, please hit subscribe and like, come to that. Now next, GCC banks are investing heavily in AI, but can their existing technology infrastructure keep up? We need to look at what banks need to do to modernize as AI becomes increasingly central to financial services next. So the Digital Commerce, Retail, E-Commerce, Payments and FinTechs Exhibition, Seamless Middle East, 2026 began yesterday. It runs until tomorrow at Dubai World Trade Center. Machahit Gundebahar is there. He has more than 25 years of experience across banking tech and FinTech. He's the co-founder and CEO of the global banking platform, Fimple. Joins me from the show.

Machahit, good to be talking to you this morning.

Machahit Gundebahar (1:00)

Thank you, thank you, Tim, for having me. Thank you.

SPEAKER_1 (1:04)

You're welcome on the program. Now, at Seamless 2026, every financial institution is talking about AI transformation. From your vantage point, you oversee core banking platforms. How wide is the gap between AI ambition and the reality of those kind of legacy back-end systems?

Machahit Gundebahar (1:29)

Yeah, yeah.

Very good question, Tim. I mean, as you mentioned, AI is a big topic and everybody's agenda. And but the thing is the AI models, AI systems must be running on proper, well-defined systems. I mean, most of our, most of banks in our region having legacy boards, then they suffer a lot to implement their AI dreams. I mean, AI systems must have proper AI API first, modern system. I mean, you know, at the end of the day, with AI, you are triggering, you are deciding something and you are triggering that thing. So with the legacy course, you cannot do that, I mean, models.

So you need to have a modern API first, I mean, microservice enabled system to achieve your AI goals in the financial industry.

SPEAKER_1 (2:40)

I mean, across the region, banks are investing heavily in all sorts of AI systems, co-pilots, automated underwriting, hyper-personalized bots for customers. What needs to happen to the underlying technology before, you know, a bank can get the full value from the systems they're investing in?

Machahit Gundebahar (3:06)

Yeah, again, it comes to core technology. I mean, for example, banking and financial industry providing services both for individual and corporate work. So, it is a basic platform, and AI runs and optimizes that platform on top of that. So, integrating AI, you need to have a modern microservices API for system. Again, as I mentioned earlier, your AI agents or your AI models decide something and initiate that thing.

That initiation, that trigger must happen in your core system. That's why you need to have API or process or composable system. That trigger can be API or process, that's why composability matters a lot. I mean, your banking system, in your banking system or financial system, the bank itself can create a personalized products and processes to your targeted customers or even targetable individuals.

In real time, data streaming is very, very important. I mean, with AI, instantly you can decide something, trigger that thing, orchestrate, and ensure data stream across platform, instantly relying on your core system. Finally, I can name it, native notification services must be there in your core system because, I mean, you decide something, you trigger that thing, but you need to notify customer also. So, it must be there. These are key elements I can name.

SPEAKER_1 (5:14)

Okay. So, simply put, legacy infrastructure limits the returns from AI investments that these organizations are making.

AI needs instant event-driven responses, right? Whether that's real-time fraud detection, or instant credit scoring, whatever it is. So, how do you advise banks to restructure their core databases to support these real-time machine learning workflows? Because the two have to talk to each other.

Machahit Gundebahar (5:54)

Yeah, Tim, again, great question.

There are a lot of new players entering the market. I mean, for those guys, it is easy to decide that question, because they can go with the modern technologies like simple AI native, AI energy, we could also use API ways, propose a new segment. But for incumbent plans, they already have legacy policy. I mean, they have existing, nearly decades, two decades, three decades existing forces to the customer's system. So for those events, we recommend not replacing all of the four systems. A single day, it's not takes years and years. It takes double digit, maybe triple digit million dollars in experimentation, conversion, and technology. So we recommend them keep their existing legacy core, position, use that core for business as usual purposes. Next to it, position modern core banking system like PIFO, which is API first, and Composable, this and that. So do some integration between full course and achieve your AI goals and modern business. Like AI is, we are discussing with AI, but in the market, banking as a service or platform or open system in banking also big topics. So with having a modern core, they can do their business, those new modern business with a new core, and they can continue their business as usual from their legacy core. I mean, we call it a side core approach. With side core approach, they don't have to invest a lot. They don't have to do big risk, big bank projects.