Melton Building Society’s AI Strategy and Governance

Gareth Everly

Alright, so picture this: you're walking into a bank, and instead of a human at the counter, you've got this AI assistant ready to help you sort out your finances. Seems futuristic, right? But for Melton Building Society, it's not science fiction—it's the direction they're heading. And they're not just rushing in all gung-ho; no, they’ve got a plan. A responsible one.

Ella Spencer

The whole approach starts with their vision, and it’s a big one. They aim to transform operations top to bottom with artificial intelligence—think customer engagement, fraud detection, better credit risk scoring. But here’s the kicker: they’re doing it responsibly, making sure it’s all wrapped up in trust, ethics, and those ultra-critical regulatory standards. They’re not simply throwing AI at problems and hoping for magic—it’s a calculated effort.

Gareth Everly

To manage this, they’ve set up three, yep three, governance committees that tackle different aspects of this journey. First, there’s the AI Steering Committee, which essentially directs the entire strategy, keeping an eye on the big picture. Then there’s the AI Ethics Committee—it’s like their moral compass, ensuring, well, that the AI doesn’t lose its way ethically. And finally, the Data Governance Board, which handles all the nitty-gritty of data security and privacy. It’s all very structured, which, let’s be honest, is how it should be with something this monumental.

Ella Spencer

Now, the genius of their approach is in the baby steps—they’re running these pilot projects to test the waters before diving in headfirst. For starters, they’re piloting AI-driven customer service. Picture automated systems that, while boosted by AI, still feel intuitive and actually helpful. And then there’s fraud detection, which is about catching those sneaky transactions in real-time. Plus, credit risk scoring that isn't just fast but super precise. These are all being tested in what they’re calling ‘controlled environments’. I mean, it’s like setting up a test run on a smaller track before taking the car out onto the highway. Makes sense, doesn’t it?

Gareth Everly

But it's not all smooth sailing. These early projects are where they iron out the creases—seeing how the systems work in real scenarios and figuring out where they might, you know, stutter. That way, when they roll out AI on a larger scale, they’re not stumbling over hurdles they could’ve spotted early. And all of this is done with one eye firmly on those pesky regulatory standards. Compliance isn’t an afterthought here; it’s baked in from day one.

Ella Spencer

And the result of these efforts? Well, it’s not just about making the bank more efficient—it’s about trust. I mean, would you really trust an AI decision if you couldn’t peek behind the curtain and see how it works? That’s why explainability and fairness play such a huge role in everything they’re building, but I’ll unpack that in a bit…

Gareth Everly

Now, trust and fairness—it’s not just nice to have when it comes to AI; it’s, well, absolutely essential. Melton Building Society understands this in a big way, and, honestly, it shows in how they’ve set their goals. Take this for instance: any bias in their AI systems? It can’t go over 2%. Not 10%, not even 5%—just 2%. It’s all about ensuring that these systems treat everyone fairly, no matter what—whether it’s scoring credit or identifying fraud.

Gareth Everly

And fraud detection, by the way? They’ve got a benchmark for that too. False positives need to stay under 5%, which, let me tell you, is a tricky balance because, you know, you’re catching fraudsters without flagging innocent transactions. But it’s worth it. These kinds of safeguards? They keep the AI honest, and more importantly, they keep it trustworthy.

Ella Spencer

But fairness isn’t just about the algorithms. No, it goes much deeper than that. Imagine you’re a customer, and an AI denies you a loan. What then? Melton believes you should, at the very least, know why. That’s why they have this ‘Right to Explanation’ policy. It’s where they, basically, peel back the curtain a bit and show you why the decision was made. And if you don’t agree with it? You can—you can escalate it, ask for a human review. Transparency, plain and simple. They’re even considering making full transparency reports accessible to customers. It’s an approach that says, “We’ve got nothing to hide,” and that’s reassuring, isn’t it?

Ella Spencer

Of course, no grand vision works without the people behind it, right? And that includes the staff. Here’s where training comes in. Every employee, not just a select few, is trained on ethical AI practices—regular training, so that they’re always, you know, in the loop about new developments. Leaders get extra training too, because, at the end of the day, they’re the ones guiding the ship.

Gareth Everly

And then there’s this whistleblowing mechanism, which, honestly, is brilliant. If staff members spot something dodgy, they can raise it anonymously. It’s a bit like giving employees a secret hotline to call out concerns without fear—bias, unethical decisions, you name it. Those reports go straight to the ethics committee for an objective review, which—it’s a system that really ensures issues don’t get swept under the rug.

Ella Spencer

All this? It’s how Melton’s turning AI into a tool people can trust, not just within their walls but out there with customers. And it’s not perfect—it probably, well, never will be. But the point is, they’re working tirelessly to get it as close to ethical and transparent as possible. That being said, the targets they’re setting don’t stop here; they have a roadmap that looks way beyond just these first steps...

Ella Spencer

So, let’s talk big plans—because Melton Building Society has some. And by big, I mean ambitions that stretch over the next five years. We’re talking about goals like using automation to cut compliance processing times by more than 50%. Imagine that—where painstaking paperwork gets streamlined into mere clicks, freeing up people to focus on, well, the more human elements of banking.

Gareth Everly

And customer satisfaction? They’re shooting for an 80% or higher satisfaction score in AI-driven interactions. That’s no easy feat. It means they’re meticulously refining their systems to not just meet expectations but exceed them. And this isn’t about replacing the human touch entirely; it’s about complementing it. The AI handles the repetitive bits, sure, but those deeper, more nuanced conversations? They stay human-led. It’s a collaboration, really—not a competition.

Gareth Everly

But here’s where Melton isn’t taking any chances: cybersecurity. With AI, it’s not just about fighting fires when they spark—it’s about stopping them before they even start. Their strategy includes some pretty advanced measures, like detecting anomalies in real-time and running relentless tests to make sure their systems are bulletproof. And everything aligns with GDPR regulations, by the way, so your data? It’s not just secure—it’s sacred. They treat it like gold, knowing that trust is built on privacy.

Ella Spencer

What I find fascinating, though, is how all of this—these ambitious KPIs, these fortified safeguards—leans on balance. It’s not just about pulling the shiny lever of innovation; it’s about weighing every decision against governance, compliance, and, ultimately, responsibility. You know, like crafting a pocket watch—every gear, every spring, has to be perfectly calibrated, or the whole thing just doesn’t work.

Ella Spencer

In the end, Melton Building Society isn’t aiming for perfection. No one is. But they’re setting benchmarks and fiercely chasing them, all while keeping a tight grip on ethics and transparency. And that’s the kind of commitment that makes you think, “Yeah, I’d trust these folks with my money—and my data.”

Ella Spencer

And that, my friends, wraps up our deep dive into Melton’s journey towards AI-enabled banking. It’s ambitious, yes. But it’s also grounded in responsibility and care. On that note, thanks for listening, and, as always, stay curious. Until next time!