In finance, the sexiest thing is for AI to be boring.

Not many people would say that out loud, but David Hardoon might agree with the sentiment.

As Global Head of AI Enablement at Standard Chartered, David has built his career on showing that the most powerful form of artificial intelligence in banking is the kind that blends quietly into the background.

While the rest of the world obsesses over generative breakthroughs and futuristic trading bots, he is more interested in the everyday, the unglamorous, carefully governed AI that keeps banks resilient.

During a recent conversation, he quipped that we should “make AI boring again”, not because it lacks excitement, but because that’s how it becomes useful.

“The real value of AI emerges from grounded, practical applications that may seem unglamorous but deliver sustainable impact,” he said in an interview with Fintech News.

For him, “boring” means trustworthy.

It means systems that don’t crash under pressure, models that don’t introduce bias, and processes that make banking a little faster and safer every day.

In a world that treats AI like a spectacle, David’s philosophy is refreshingly pragmatic.

Make it stable first, then make it smart.

The Unsexy Side of Financial AI

For banks, being “boring” should not be taken as an insult.

Dullness can be a virtue as this industry more often or not, thrives on predictability. Rarely on surprises. The industry operates in a world where errors have consequences that ripple through markets and affect lives

Thus, it is why David believes that the best AI systems are those built on strong governance and clear accountability. For Standard Chartered, those principles aren’t something to talk about.

No, to them, it is something to live by in every AI project.

He points to the FEAT framework (fairness, ethics, accountability, and transparency), which he helped pioneer years ago with regulators in Singapore.

These principles shape how the bank designs and deploys AI, ensuring every model is explainable and aligned with business goals.

“Effective and safe AI can come across as boring”, he explained.

He said that this is because it focuses on robust governance and seamless integration into core operations.

David believes that the most powerful tools should be able to enhance everyday processes like risk management and compliance, reducing errors and building long-term trust.

In other words, the true sophistication lies in the discipline, not the drama.

Starting with the Problem, Not the Hype

Rather than beginning with technology, Standard Chartered starts with the business problem it’s trying to solve. David’s team often asks simple but powerful questions before they begin any project.

What slows us down? Where do the errors happen? Which tasks waste people’s time?

When the bank’s trade finance operations faced delays caused by manual document processing, the team didn’t look for the flashiest solution. They built one that worked.

And it did. The result was the Trade AI Engine, a system that automatically extracts key data from scanned trade documents, cutting hours of work and improving accuracy across markets.

“This wasn’t about cutting-edge tech but about iterative refinement,” David said.

His team tested ideas carefully, built in ethical checks, and made sure every solution could scale without breaking compliance. The result was a tangible impact with better efficiency and stronger risk control.

You see, it’s not the kind of AI that makes headlines, but it’s the kind that sticks.

Why “Cool” Can Be Costly

The idea behind this interview came when I caught a glimpse of what he said during one of the many Standard Chartered media meetings in Kuala Lumpur.

At that time, the Global Head of AI Enablement at Standard Chartered was seen to often warn us against the allure of “cool” AI. The kind that looks impressive in a demo but delivers little in practice.

He likes to say that hope is not THE strategy. Hope is part of the underlying strategy process.

David has seen what happens when hype drives experimentation. Most AI pilots fail to scale, either because they don’t align with real business needs or because they ignore governance.

During that discussion, he described how his team approaches projects with a sense of discipline rather than excitement.

At Standard Chartered, AI is now embedded across about 15 thematic areas.

It can be seen from cybersecurity to wealth management, all the way to internal operations. Each initiative is assessed for its value, feasibility, and impact.

He believes that flash is never the priority. Function is.

Building Trust Through the “Boring” Bits

The rise of AI has also brought as many concerns as opportunities. Banks are now navigating deepfakes, synthetic fraud, and new cyber threats that challenge long-held ideas about trust.

For David Hardoon, the answer isn’t to fear the technology but to engineer it carefully. He often points out that AI itself can be part of the defence.

“AI can find AI,” he said.

This refers to how most banks now use machine learning to detect fake voices or manipulated media. A proof that the same technology that creates risk can also help contain it.

So that is where trust ties it down. Trust, in his view, isn’t something you declare but rather something that you design. It has to be built into every layer of design.

There’s also something deeply human in David’s approach. He doesn’t treat AI as a force that replaces people, but as one that amplifies them.

Across the bank’s 80,000 employees, upskilling is as much a part of the AI strategy as the technology itself.

David explained that for employees, AI has become part of job security. It frees them from repetitive tasks and gives them room to focus on more meaningful, higher-value work.

Sometimes, that capacity comes from the smallest improvements. David shared a really, really boring example, which is fixing payment errors. A missed word in a transaction field can cause an entire payment to bounce.

With AI, the system can automatically detect and correct it. Yes, it’s not that glamorous, but it’s efficient.

Multiply that by millions of transactions, and the impact becomes enormous.

Making It the Staple Diet

David often says AI should become part of banking’s “staple diet”.

When something becomes ordinary, it becomes reliable. And when it becomes reliable, it earns trust.

That’s how he wants AI to exist within the bank. Not as a headline-grabbing initiative, but as an invisible utility that powers everything behind the scenes.

To him, success shows up in the details, in systems that work so reliably that people trust them, regulators respect them, and clients barely notice them.

“True success builds organisational trust, fosters sustainable innovation, and positions AI as a competitive advantage,” he said.

The Beauty of Being Boring

In the end, David’s message is simple. AI doesn’t have to dazzle to make a difference.

In finance, the technology that lasts is the one that quietly works. The kind that improves processes without drama, manages risk without noise, and builds trust without fuss.

Maybe that’s what makes it beautiful. Not the hype, but the discipline. Not the promise of disruption, but the reassurance of control.

After all, in finance, a little dullness keeps the lights on.

All work and no play doesn’t make AI a dull boy; it makes him dependable.

Featured image: Edited by Fintech News Singapore based on an image by pixelshunter via Freepik.