We’ve just surpassed two billion in debt facilities on our platform. Now, that number itself does not mean a lot to me, because there's some facilities that are huge, others that are small, right? And the complexity might be totally different.

We have some customers where it's huge facilities, but it's fairly simple stuff like auto loans, and then one of our smallest customers, they do income share agreements for students internationally. It's a crazy, complicated interest calculation.

It's hundreds of thousands of data points every hour that we process. So that's incredibly challenging from a tech perspective. So the number is good. It's impressive. It shows that we are being trusted, but I'm more excited about the use cases behind that, right?

I think where AI excels is in trying to emulate what could be a human interaction.

And, by definition, what we do, and specifically do for mortgages, is dominated by human interaction. Across the world - so we're talking not only about emerging markets, but developed markets as well.

You have mortgage brokers that talk to customers. They do simulations. They explain what the bank offers that they can get approved for, and so on and so forth.

So I think the real need here was how do you bring that human experience into a place where you have thousands of islands and very remote locations and where the people buying properties are not necessarily concentrated around the large cities.

But what they ended up doing is, okay, if you want to take this thing without a credit card, bring your salary statement, bring your bank account statement - I don't have any of this, right?

One of the huge issues was, and still is, the access to finance in Laos. There's hardly any infrastructure, too. You don't find a paved road everywhere.

And the people live in their village, in their community, but they have to travel like two hours to the next bank. And then they talk to this bank and they want to get a loan and it's not possible.

Every one of our customers, though, is credit scored. we have 16 data points, starting with age, profession, if you live close to a border with a lot of trade between Thailand and Laos, might be very different than to a very rural place in the middle of the Mekong - we have some islands in the Mekong that don’t have electricity, don't have Internet, but they have a village bank.

It doesn't matter if you're from China or if you're from Brazil, if you're from the US and from UK, from Italy. There's people with ideas, there's innovative founders, and then there's other people that, like myself, I needed a job, so I can't necessarily become a founder, my life trajectory has run differently, but then equally, I have this creativity in my brain that I love sharing with peopl because I know that the founders that I share with and the passion that I have for the things that I actually invest in, it helps them accelerate certain things.

And potentially, I'm the crazy one that goes to conferences as well and then speaks at places. But I know a lot of people that are similar to me, that are very good at their day job but also want to invest.

It unlocks two other elements :the first one is the real-time sharing of information which otherwise would be impossible, but the second one is that when we are connected by API to a financial institution, every time we ping their database, they actually have a record that allows us to pay them. Essentially, we pay on a portion of the fee that the network captures back to the same financial institutions.

Now, that means that they can either run this as a data monetization channel - and by the way for some of the landers that we work with in the Philippines that's been the case - or it also means that they can use the same payments for then increased consumption through the platform. The increased consumption then reduces their data pool cost, and ultimately that makes it two to three times cheaper than any other alternatives.

In the world of crypto, a few months can be a lifetime, and, in the most recent few months that’s not been the easiest lifetime, and yet, Milo has just issued its largest single transaction ever: a $12 million crypto mortgage. The demand is real, from high net worth individuals buying homes with Bitcoin to clients tapping home equity to buy more, and, if anything, the recent dips in crypto prices reflect a story of growing resilience rather than one of growing volatility, and that's a very good thing for the industry.

Smarter advice leads to smoother lending, so today I am sitting down with James Tucker, CEO at Twenty7tec Group, talking about how his solutions, helps lenders maximise product visibility, streamline applications, and improve adviser engagement.

Banks certainly don't lend as much as they should, but if you talk to the average banking executive, they want to. Lending is growth, at the end of the day, lending is one of the best, biggest, most efficient growth drivers.

I think my point of view on the banking sector, specifically community and regional banks, have shifted where there is this wild aspiration to build larger lending functions…. but I think they're looking for a way forward.

All financial decisions were being made like this, by a banker in your village who knew you and your family, he knew if you were a responsible person or not at all, and that's what decided if you are eligible or not for something that the bank offers. The thing is now, with the further digitalisation, it has dehumanised, actually, the world, all these kinds of personal relations and personal insights are being vanished away because everything has to be made efficient and fast.

What is really important for me, about Most Probably, is that I want to be known as a company that can connect dots and look at complex problems and bring it to a solution that is workable, implementable, and has impact.

I like getting people together from different areas, getting people from sales, credit and and channel to speak. I'm very passionate about having people understand one vision and having the outcome be beneficial to all. So, with my executive background, together with the detailed background I have in statistics, analytics, etc. I am mentoring and coaching up and coming executives.

60% of businesses just gave up halfway through a loan application, which is crazy.

I think that indicates how much of an obstacle the process is in itself, which I think then speaks to a system that is built, probably more for institutions in terms of debt funding, rather than a system that is built to support small businesses.

But all we're really trying to do is answer three simple questions for clients. Is this presented identity, a genuine identity? Am I interacting with the owner of identity? And are there any risk factors associated with that identity I've been presented with.

In the 90s, inflation in Brazil in one year was over 1,000% so literally, if you got your money today and you didn't use it, you didn't run to the supermarket, you buy it, you lost money. And so Brazilians really got good at moving money fast and spending fast. And the banks had to learn how to do those things since the 90s, the liquidity of the system, the security of the system, the solvency of the back like all those things, had to really be at a very good level, otherwise the mess would go into the economy

I think one of the most challenging parts of being a business, it doesn't matter what size you are, is that you tend to place a portion of who you are as a person, your value, in the outcome of whether somebody pays or not.

And you know, as much as you like to try, if you've got enough people not paying, it does actually become a demoralising feeling.

I think people are realizing that it's not always someone's fault if they are having financial difficulties, and I think that message is changing, albeit sometimes I still have frustrating conversations with people who don't necessarily see it that way.

And I think overall, the lenders, the collection agencies, debt management plan providers, whoever it might be, are wanting to be able to treat their customers in a better way, give them the experiences that they deserve, but they just don't have the systems to power that.

If you're an individual and you care about the climate, the biggest impact you can have is what you do with your money: where you deposit your money, how you spend your money, and where you invest your money.

That is by far the largest impact you can have. Much more than buying a solar system, putting on your house, though, that's a good thing to do, and it's much, much more, by the way, than buying an electric vehicle, though that is also a good thing to do.

And this is not a niche market. Fully 40% of US adults identify themselves as highly concerned about the climate and seeking ways that they can make an impact in their own life.

Unbankable is an investigative documentary exploring whether Africa's innovation, tradition, and tech can revitalize the West. It examines mobile money, digital lending, and Bitcoin, challenging economic norms and amplifying voices from the Global South.

One of the UK banks that we work with, they have 17 lending systems. That’s really complicated to work with. People can change. Technology can change. What doesn't change is the process. So you have to adapt to every banks process. Technology has to adapt to every process. So essentially, people adapt, and technology adapts. But the process is something which doesn't change, and that is something which is the learning process for everyone when you work with a particular institution.

AI is emerging as a as a transformative force, which is redefining banking: from digital lending to advisory, to research, it’s across all its different business units.

The nice thing about digital lending, really, is that you have full transparency over individual loan applications, and I feel like that, rather than buying a blind pool, or a securitization backed by some some collateral pool of loans that you don't really have an influence on, you can now, with the technology and the emergence of the digital lending segment, go way further and actually have perfect insight into what's going on in the collateral pool.

So ultimately, we are directly integrated into the underwriting systems of the originators that we work with. So essentially, we see the same data that was used from the originator to process the loan application, and that enables us to form an independent view. And in addition to that, we usually get also the entire historical track record of the originator, which allows us to then also fine tune our risk models to the specific types of products and the specific type of underwriting that the originator is doing, in order to then form an opinion on a loan by loan basis, or borrower by borrower basis,.