EP971: A trusted partner, modernising with confidence

In an interview with IBS Intelligence, William Moroney of Temenos discusses the urgent need for financial institutions to replace outdated legacy systems with flexible, modern technology. He explains that banks are increasingly adopting cloud-native platforms and artificial intelligence to enhance operational efficiency, combat financial crime, and provide tailored customer experiences. Temenos is supporting this transition by offering modular software solutions and AI-driven tools that allow for faster product launches and more secure data management. The discussion highlights a global shift toward strategic IT investment, where technology providers act as essential partners in navigating regulatory changes and digital transformation. Ultimately, the source emphasizes that successful modernization depends on ecosystem collaboration and the ability to scale innovation through a single, adaptable platform.

Transcript

SPEAKER_01 0:00

Right now, your life savings, your mortgage, and well, basically your daily transactions are likely sitting on a computer system that was uh built before the moon landing.

SPEAKER_00 0:10

Yeah, it's pretty wild to think about.

SPEAKER_01 0:11

Aaron Powell It is, because you open your banking app today and it looks, you know, incredibly sleek. You transfer funds with a thumbprint, you can trade stocks while standing in line for coffee, and it all feels perfectly modern.

SPEAKER_00 0:22

Aaron Powell Oh, absolutely. The front end is pure 2026.

SPEAKER_01 0:25

Trevor Burrus, Jr. Right. But behind that digital glass, like behind the polished user interface, the actual foundational architecture of most major banks is this web of aging, fragile, hundred-year-old plumbing. And it's uh it's starting to leak everywhere.

SPEAKER_00 0:41

Aaron Powell It really is the ultimate facade. I mean, the mobile experience is great, but the back-end infrastructure that's processing the actual money is often decades old. Trevor Burrus, Jr.

SPEAKER_01 0:49

Which is terrifying.

SPEAKER_00 0:50

Aaron Powell It is. And the strain of connecting those two very different worlds has pushed the financial sector to an absolute breaking point.

SPEAKER_01 0:57

Aaron Powell, which brings us to our mission for this deep dive. We are looking at a massive high-stakes transformation that's happening completely out of sight, right inside the financial apps you use every single day.

SPEAKER_00 1:09

Exactly.

SPEAKER_01 1:09

And our guide for this is a really revealing October 2025 big interview from the IBSI FinTech Journal. They sat down with William Moroney, the chief revenue officer of Teminos.

SPEAKER_00 1:21

Right. And Teminos is a huge titan in the banking software space.

SPEAKER_01 1:24

Aaron Powell Yeah, so they know what they're talking about. And Moroni lays out what he calls a perfect storm that's currently facing banking leaders.

SPEAKER_00 1:31

And we really need to understand the mechanics of this perfect storm because, well, it goes far beyond a standard IT headache. I mean, the core issue, what we can call the billion-dollar anchor, is the sheer financial weight of maintaining these legacy systems.

SPEAKER_01 1:45

Aaron Powell Wait, billions.

SPEAKER_00 1:46

Literally billions. Moroni points out that banks are spending billions of dollars every single year just on maintenance. Trevor Burrus, Jr.

SPEAKER_01 1:52

Just to maintain it.

SPEAKER_00 1:53

Trevor Burrus, Jr. Right. Not on innovation, not on building better features for you, but simply patching old code to stop the servers from crashing.

SPEAKER_01 2:00

Trevor Burrus, Jr. Let's uh let's untack the mechanics of that drain. Why does simply keeping a server running cost billions? I mean it's not the electricity bill. Trevor Burrus, Jr.

SPEAKER_00 2:08

No, no. It's the monolithic architecture of these legacy systems. Decades ago, banks built their software as one giant tangled web of code.

SPEAKER_01 2:17

Aaron Powell Like spaghetti.

SPEAKER_00 2:18

Exactly like spaghetti. When you have a monolithic code base, everything is completely intertwined. So if a bank wants to, say, simply update the font color on their mobile login screen.

SPEAKER_01 2:29

A super basic update.

SPEAKER_00 2:30

Right, a basic update. But they run the risk of accidentally breaking the interest rate calculator for their commercial mortgages.

SPEAKER_01 2:37

Oh wow. Because it's all the same tangled mess.

SPEAKER_00 2:39

Aaron Powell Exactly. And that tangled web is often written in languages like COBOL.

SPEAKER_01 2:43

Right, which nobody learns anymore.

SPEAKER_00 2:45

Exactly. We're facing a demographic cliff where the engineers who actually know how to read and write that specific vintage code are retiring.

SPEAKER_01 2:53

So you have banks relying on this uh increasingly rare pool of talent to manually untangle spaghetti code just to keep the lights on.

SPEAKER_00 3:01

Aaron Powell Yep. And the top-performing banks, the ones actually leading in customer experience, they recognize this is completely unsustainable. They're aggressively trying to reclaim those billions in maintenance budgets and redirect them into strategic forward-looking architecture.

SPEAKER_01 3:19

Aaron Powell Okay, but wait. If I'm running a global bank and my core system is a spaghetti code nightmare that's draining billions of dollars just to survive, I'm not going to keep nursing it along. Right. Like if my car costs more to fix every month than the price of a brand new vehicle, I just sell the car. Why don't these executives just take a sledgehammer to the mainframe, rip the legacy code out entirely, and start fresh?

SPEAKER_00 3:40

Well, because of what is flowing through that code, you aren't just upgrading a corporate email server here. You are handling the lifeblood of the global economy. You've got millions of daily transactions, payrolls clearing on a Friday morning, people's life savings, corporate trade flows.

SPEAKER_01 3:57

Okay. Yeah, that makes sense.

SPEAKER_00 3:58

If a social media platform goes offline, it's an inconvenience. If a Tier 1 bank's core system crashes during a rip and replace migration, commerce literally stops.

SPEAKER_01 4:07

It's a disaster.

SPEAKER_00 4:09

It triggers a national news crisis and immediate regulatory intervention. The risk profile is astronomically high.

SPEAKER_01 4:16

So a sledgehammer approach risks taking down the regional economy. That kind of forces the industry to find a middle ground, right? Somewhere they don't have to bet the entire farm on one massive overnight upgrade.

SPEAKER_00 4:29

Which is exactly why the industry has developed a highly specialized modernization menu. The era of the uh one size fits all software upgrade is totally dead. Good riddance. Seriously. According to Moroni, banks now generally choose from three distinct paths to untangle their infrastructure, and it's based entirely on their specific risk appetite.

SPEAKER_01 4:50

Okay, what's path number one?

SPEAKER_00 4:52

The first is full core replacement.

SPEAKER_01 4:54

The closest thing to the sledgehammer.

SPEAKER_00 4:55

It is. Some banks are willing to take that massive leap, absorb the complexity head on, and just leapfrog their legacy constraints all at once to get a totally clean slate.

SPEAKER_01 5:05

Sounds stressful.

SPEAKER_00 5:06

Extremely. But for those who cannot stomach that risk, the second option is the modular approach. Which means this is where a bank upgrades piece by piece. So they might migrate the lending processing to a modern cloud system this year, wait for it to stabilize, and then you know move the deposits module next year.

SPEAKER_01 5:24

Leaving the rest of the legacy system untouched while they operate.

SPEAKER_00 5:27

Exactly. It drastically shrinks the blast radius if something goes wrong.

SPEAKER_01 5:40

Surround and extend.

SPEAKER_00 5:41

Yeah. They leave their deepest core legacy system essentially untouched, but they deploy modern point solutions around it to handle specific heavy lifting things like digital pymets or financial crime mitigation.

SPEAKER_01 5:53

So think of it like an old vintage computer. You have a reliable but totally outdated desktop machine from like 1998. Right. Instead of opening the case and trying to physically solder new microchips onto the motherboard, which would likely destroy it, you just plug a massive high-speed modern external processing unit into it.

SPEAKER_00 6:12

Yes, exactly.

SPEAKER_01 6:13

And you use application programming interfaces or APIs as the cables. So the APIs pull the necessary data out of the old machine, process it at lightning speed in the modern unit, and push the results back.

SPEAKER_00 6:25

That is a phenomenal way to visualize it. You surround the old engine with modern technology to get 2026 performance without actually touching the fragile internal circuitry. Right. And the underlying requirement for any of those three paths is ultimate flexibility. Moroni emphasizes that a modern banking platform like what Teminos builds has to be cloud native and highly modular.

SPEAKER_01 6:47

Meaning it can go anywhere.

SPEAKER_00 6:48

Exactly. It needs to deploy wherever the bank needs it, directly on the bank's own physical hardware, in a public cloud, or through software as a service. You basically build one universally adaptable software architecture that can plug into whatever modernization path the bank chooses.

SPEAKER_01 7:03

But whether a bank replaces the core entirely or just surrounds it with external processors, they are ultimately building a modern engine. And while every modern engine needs fuel, in the financial sector today, that fuel is massive amounts of data. And the system actually braining that fuel to create forward momentum is artificial intelligence.

SPEAKER_00 7:23

Right. And Moroni makes a definitive pivot here. AI has finally crossed the threshold from just a buzzword thrown around at board meetings.

SPEAKER_01 7:32

Which we hear all the time.

SPEAKER_00 7:33

Constantly. But now it's a critical structural layer of banking operations. It is the designated tool for automating back office operations, managing crushing compliance requirements, and generating the hyper-personalized services that users actually expect.

SPEAKER_01 7:49

But wait, every app on my phone claims to be powered by AI right now. The fitness tracker, the grocery delivery app, literally everything. Why can't a bank just buy a massive enterprise license for an off-the-shelf AI model, point it at their servers, and let it run? Trevor Burrus, Jr.

SPEAKER_00 8:03

Because an AI model is only as intelligent as the environment it operates in.

SPEAKER_01 8:06

What do you mean?

SPEAKER_00 8:07

Well, Moroni points out the massive structural catch. To make AI function safely in banking, you must have highly structured data running on a modern core. Legacy mainframes store data in massive disconnected silos. So the mortgage department's data doesn't naturally talk to the credit card department's data. If you unleash a highly sophisticated algorithm into a disorganized siloed environment, it cannot contextualize the information. It can't read the room. It creates chaos. Structured data means every single piece of information is universally categorized, tagged, and instantly accessible in a uniform language.

SPEAKER_01 8:43

Right. So the AI knows what it's looking at.

SPEAKER_00 8:45

Exactly. AI requires that pristine, perfectly mapped environment to navigate securely. And building that pristine environment requires an entire ecosystem. No single bank and frankly, no single software provider can build this alone.

SPEAKER_01 8:58

Aaron Powell Which is why Moroni brings up the concept of hyperscalers.

SPEAKER_00 9:02

Yes, hyperscalers. These are the massive global cloud infrastructure providers. Microsoft, AWS, Google. Teminos relies on incredibly deep collaborations with these companies. Trevor Burrus, Jr.

SPEAKER_01 9:12

Because of the processing power.

SPEAKER_00 9:13

Exactly. The raw computing power required to process structured financial data and run generative AI models in real time is staggering. Banks cannot build those server farms themselves. Trevor Burrus, Jr.

SPEAKER_01 9:23

Right. They're banks, not tech giants.

SPEAKER_00 9:25

Aaron Powell So the ecosystem brings together the cloud compute of Microsoft or AWS, the foundational banking software of Teminos, and specialized FinTech partners. That combination is what creates this secure environment where open APIs and embedded AI can actually function. Aaron Powell Okay.

SPEAKER_01 9:44

So we're talking a lot about architecture and ecosystems, but I want to look at the actual output. When you combine structured data, hyperscalar cloud power, and a modernized core, what does the resulting AI actually do in the wild? Like how does it change the business of banking?

SPEAKER_00 10:00

Well, the source gives us two incredibly concrete examples of this technology in action. The first is designed for the revenue generating side of the bank. It's called the product manager copilot.

SPEAKER_01 10:10

Copilot. Okay, how does an AI actually build a financial product?

SPEAKER_00 10:14

Well, think about the legacy way of launching a new type of savings account or, say, a specialized small business loan.

SPEAKER_01 10:20

Lots of meetings, I imagine.

SPEAKER_00 10:21

Oh, endless. It used to require months of cross-departmental meetings, actuaries modeling risk on spreadsheets, compliance reviews, and manual coding just to get it into the banking app. Thanks. But the Copilot is a generative AI tool. Teminose co-developed with design partners like BIL in Europe and Commerce in the U.S. It ingests the bank's live data parameters, current market interest rates, historical demographic data, risk thresholds, and regulatory constraints.

SPEAKER_01 10:47

And it just synthesizes all of that to generate the product framework instantly.

SPEAKER_00 10:51

Aaron Powell Exactly. A product manager can ask the AI to model an optimized loan structure for a specific demographic in a specific region, and the algorithm instantly cross-references the data to generate a viable, compliant product ready for testing.

SPEAKER_01 11:05

Wow.

SPEAKER_00 11:06

Yeah, it turns a six-month long cycle into a fraction of the time.

SPEAKER_01 11:09

Aaron Powell That is insane. Okay, so that covers product generation. What is the second real-world application?

SPEAKER_00 11:14

Aaron Powell The second example focuses on risk management. It's an AI agent specifically designed for financial crime mitigation, co-created with a European Tier 1 bank.

SPEAKER_01 11:22

Financial crime. Okay.

SPEAKER_00 11:23

And Moroni shares a metric here that is highly significant. It is a regulator-accepted tool proven to reduce false positives and sanctions, screening down to just 2%. Aaron Powell.

SPEAKER_01 11:33

Let's focus on that mechanism. Because massive global banks already have anti-money laundering software. Why is a 2% false positive rate such a monumental shift?

SPEAKER_00 11:44

Because legacy screening software relies on really rigid, static if-then rules. Like what? Well, for example, a legacy system might have a hard rule. Flag any international wire transfer over$10,000 to a specific list of countries. It is incredibly blunt.

SPEAKER_01 12:01

Aaron Powell Okay. So if I legitimately buy a vintage rug from an overseas vendor, the legacy system flags me.

SPEAKER_00 12:07

Yep. Your transaction is frozen, a human investigator has to open a file, review your account history manually, and clear the flag.

SPEAKER_01 12:14

Which takes days and completely ruins the customer experience.

SPEAKER_00 12:17

And more importantly, it wastes the bank's investigative resources. When an AI agent drops that false positive rate to 2%, it's because the algorithm isn't relying on blunt rules. It is analyzing massive behavioral context in real time.

SPEAKER_01 12:30

Context is key.

SPEAKER_00 12:32

Exactly. It looks at the wire transfer, but it simultaneously sees that you recently closed on a new house, you have been browsing furniture websites, the vendor is a verified merchant, and the transaction matches your historical spending velocity.

SPEAKER_01 12:47

So it connects all the dots.

SPEAKER_00 12:48

Instantly. It synthesizes 100 data points instantly to confidently categorize the transaction as legitimate.

SPEAKER_01 12:55

And Moroni describes it as operating with human-like precision. It's basically replicating the nuanced judgment of a human investigator, but doing it on millions of transactions per second.

SPEAKER_00 13:07

Right. It filters out the noise so the actual human compliance officers can focus entirely on dismantling sophisticated real-world financial crime network.

SPEAKER_01 13:16

It is the ultimate application of a modern core.

SPEAKER_00 13:19

It really is.

SPEAKER_01 13:19

Yeah.

SPEAKER_00 13:20

The AI is acting as a highly intelligent shield, but it can only do that because the data feeding it is structured and instantly available via those cloud APIs we talked about.

SPEAKER_01 13:29

Aaron Powell Okay, but deploying an algorithm like that on a local server is one thing. We're talking about massive sprawling financial institutions spread across different continents.

SPEAKER_00 13:38

Yeah, it's massive undertaking.

SPEAKER_01 13:39

Rolling this technology out globally introduces an entirely new layer of complexity. Deploying a cloud native platform in the European Union under strict GDPR data privacy constraints is wildly different than deploying it in the United States or the Asia-Pacific region.

SPEAKER_00 13:56

Very different. Trevor Burrus, Jr.

SPEAKER_01 13:57

How does a technology provider manage the execution of this without breaking the bank's ongoing operations?

SPEAKER_00 14:02

Aaron Powell Honestly, execution at scale is arguably a bigger hurdle than writing the code itself.

SPEAKER_01 14:08

I believe it.

SPEAKER_00 14:08

Moroni emphasizes that Teminos had to fundamentally redesign their operating model to handle this global push. They collapsed the traditional silos between the people selling the software, the people installing it, and the people servicing it.

SPEAKER_01 14:21

So they unified everyone.

SPEAKER_00 14:23

Right. They brought sales, service, and delivery under one umbrella aligned directly to the customer's lifecycle. Trevor Burrus, Jr.

SPEAKER_01 14:29

Meaning the engineers designing the implementation are entirely in sync with the team providing the ongoing technical support.

SPEAKER_00 14:34

Aaron Powell Exactly. And that structural alignment allows them to move with incredible speed. Moroni notes that in just the first half of the year, they successfully supported 151 customer go lives across all their regions.

SPEAKER_01 14:48

Aaron Powell Wait, 151 go lives in six months?

SPEAKER_00 14:50

Yep.

SPEAKER_01 14:51

That includes the full core replacements, the modular upgrades, and those complex surround and extend implementations.

SPEAKER_00 14:57

All of them. It proves that this modernization push is not restricted to Wall Street or massive Western hubs. The momentum is totally global. In North America, they're leveraging an innovation hub in Orlando to co-create these AI solutions directly with clients. Nice. And in Europe, they're onboarding institutions like Aldermore Bank and Money Corp.

SPEAKER_01 15:18

Aaron Powell And regarding the differing regulatory environments, we mentioned like the GDPR constraints versus local mandates in other regions.

SPEAKER_00 15:25

Aaron Powell That really highlights the genius of a modular cloud native architecture. You build one universally robust core engine, but you swap out the localized compliance and reporting modules depending on where the software is actually deployed. This allows them to rapidly scale across Latin America, the Middle East, Africa, and the Asia Pacific region. Because every market, regardless of local regulations, demands the exact same underlying digital first capability.

SPEAKER_01 15:51

Aaron Powell That makes total sense. Right. Then we explored the modernization menu, seeing how banks avoid catastrophic risk by migrating piece by piece or by using APIs to plug modern processing power into their vintage cores.

SPEAKER_00 16:18

And we established that AI is the necessary fuel for this modern architecture, but it fundamentally requires structured data and partnerships with massive hyperscalers like AWS and Microsoft to function.

SPEAKER_01 16:29

Right. And finally, we saw how that combination of structured data and cloud power allows banks to deploy generative tools that build products in seconds and contextual algorithms that screen financial crime with human-like precision.

SPEAKER_00 16:42

Which honestly leaves us with a fascinating and slightly provocative thought to mull over.

SPEAKER_01 16:47

Oh, what's that?

SPEAKER_00 16:48

Well, consider the trajectory of the technology we just discussed. We know that these modernized cloud-native core systems are absorbing and structuring every single data point of your financial life. Yeah. We know they're running algorithms capable of nuanced contextual analysis. So what happens when the banking AI becomes so advanced and so intimately familiar with your spending velocity, your income shifts, and your life changes that it begins predicting your financial needs before you even articulate them?

SPEAKER_01 17:18

Oh, wow.

SPEAKER_00 17:19

So if the algorithm sees a sudden shift in your grocery spending toward baby formula or a pattern of visits to hardware stores, does the AI instantly generate and offer you a highly optimized 529 college savings plan or a customized home equity line of credit the moment you authenticate your app?

SPEAKER_01 17:36

That is that is wild. Will the architecture powering our banks soon understand the trajectory of our financial futures better than we do?

SPEAKER_00 17:43

It's definitely a distinct possibility.

SPEAKER_01 17:45

It is a stunning realization of just how powerful this infrastructure is becoming. Well, thank you for joining us on this exploration of the invisible machinery, quietly analyzing and powering your daily finances.

SPEAKER_00 17:58

It's been great.

SPEAKER_01 17:58

Next time you tap your phone to pay and the transaction clears in half a second, remember the massive AI-driven ecosystem processing that data right behind the glass. Keep wondering about the plumbing hidden in the walls, and we will catch you on the next deep dive.