Each time where I think that this cross border space between Brazil and the world has reached its maximum I'm wrong: every year it just keeps growing steadily and steadily and steadily.

79% of Brazilian consumers typically would divide their purchases into instalments. So this is a reality has been a reality. Now, we are also integrated with NuPay, which offers the user the capability to make a purchase with an offshore motion, and have the interest rate defined by no bank itself in the checkout process.

What we're focused on is to make the financial products available for merchants that don't have a local entity and a local structure in Brazil, so that they can great for the consumer base the same experience that our local ecommerce player can provide.

It's another excellent question, because I think there's a lot of discussion about big data and AI and machine learning. And they go together well, big data and machine learning, but they're not the same thing.

A lot of what gets done with machine learning in our industry is applying very nonlinear methods to the same old data. In fact, everything I've talked about so far has been more intelligent use of the data you've always had, Building Better models of your business and of your product.

If you have unique data, that's great. And often we find unique datasets in finance companies, where they're doing some kind of specialty lending. You know, one of my favourites for a long time was a group that was looking at point of sale loans for cruise ship tickets.

February 24 2022, was, well, the date of a big change for Ukraine as a whole.

And for Neofin as a product, Neofin as a business, we were celebrating at the beginning of February 2022, we were celebrating becoming break even - on our own, being a fully self-funded business. On February 25 2022, we realised that we're nothing close to breakeven, because most of the customers at that time were Ukrainian financial institutions and Ukrainian banks.

On February 2024, we have received about 20 emails from our customers, saying that we're stopping our lending operations because nobody knew how long the world will last. Nobody knew how resilient the Ukrainian financial system is. After the war, I think that it's one of the most resilient financial systems, with all that it has survived, but at that time, nobody knew about that. So we just received about 20 emails from the key customers saying that they're closing their their lending operations, and they just stopped paying.

And we sat down with a team, we understood that we had a team that we were gathering all over Ukraine and all over the world, we have the little dev Centre in Kuala Lumpur, we have the little development hub in Germany, and Ukraine. These are all the financial talents that would definitely want to keep inside the company and been fully revenue funded, we would not be able to do that.

The customer sees three numbers: that's the amount they will be getting, which is, let's say they are getting a million pounds; the fee they have to pay, let's call it 10%, so they have to be £100,000; and what percentage of daily sales the lender will be taking. And let's assume 15%. So from customer's perspective, they have to pay £1.1 million pounds to the lender at the rate of 15% of daily sales.

It can take three months, it can take six months, it can take 18 months. Yeah, so the repayment term is not fixed.

Why customers love it is because they just assume they have made 85% sale and the 15% will go to lender, they don't have to worry that I have to pay 100,000 a month, and I didn't make a sale this month. And what do I do now?

Most decisioning systems rely on an opaque patchwork of siloed teams and data streams with insufficient oversight and control.

Many decisions, therefore, back to the tech line that you just mentioned, rely on guesswork and instinct. And this leads to bad decisions, and costly mistakes and disappointed customers.

This is why we founded Taktile in 2020 to change that.

Taktile has offices in New York City, London, and Berlin and serves as the backbone for risk, for pricing, and fraud teams across financial services. It enables decision authors to enrich internal signals with data from our rapidly growing data marketplace and flexibly express their desired decision logic - and all of that without actually requiring engineering support.

The paradigm of 'let's collect as much information on a customer ahead of time, try and score them, and then provide them with an unsecured product'. We just don't think that works as well as putting an asset in someone's hands, asking them to pay a small deposit. And knowing that once they have access to that smartphone device, it's actually going to improve their ability to make a living. It helps them power the hairdressing salon and helps them advertise their business on WhatsApp, you're actually improving their ability to earn a living and also then to pay back the instalments just a much more compelling and sustainable model for working in the markets where we want to have an impact.

I mean, behind this there is a very sophisticated predictive credit model and we make adjustments all the time to pricing and instalment plans, and we have a lot of investment on the connected estate IoT side. And our loan book actually has been remarkably consistent. And particularly when it looked over the last three years, despite massive disruptions, and it's also been resilient in the face of high inflation.

What happened was that, when we started providing the service, we guarantee the bad debts in the service. And that's why we start actively use different kinds of analytics to develop the different kinds of scoring systems. And these scoring systems will work very fast on the fly will make the scoring on the fly. We start from the basic one, and then we start to improve it till we now use machine learning for our scoring.

The technological approach for this task grows year by year.

In the first three days we provided over 700 credits in Azerbaijan with our first operator - we were not expecting such success.

We're talking in India of about over 50 million customers. So numbers are huge.

And this is only in India we're talking about. But even here, in Canada, also, you have some microfinance, a lot of people are involved in this. And there's some very large institutions in India, which does this.

And I happened to be in a room where there was, I guess, $3 billionaires. And I said to myself, 'why am I a room full of Nigerian billionaires celebrating Nigeria, and the only thing I have to offer them is other people's businesses to invest in, right? Like, why don't I have a business for them to invest in? Why don't I have more equity in the things I'm doing?

I was very young. I was very hungry. So, knowing that, I wanted to have a deeper and richer relationship, I then presented an opportunity to the firm I was working with and to other investors, and I said, hey, I want to do this thing, this is a business.

What we do see is, working with larger providers, a real growth in adoption. If I think about the three months worth of data, live data, that we've got in the bureau - so December into January and Feb - interest free, predominantly online, for a term of no more than three months. There we see 3.8 million unique customers.

A big number, right? And they've made 50 million transactions, spending almost 20 million pounds. And it's not just your Gen Z. It's not just your Millennials, it's across all demographics.

And actually the fastest growing demographic is the 35 to 44 age band. Suddenly, I'm now just outside of that, but it's reflecting the point of becoming more mainstream, right? This is established, right? It's here to stay.

But actually, I'm going to defy the odds, I'm going to still find alternative ways to grow my business.

And they've come to us, we've got them the funding products they need. And then the same banks that said no to them when they first started, now that they're doing 2/ 3/ 4/ 5/ 10 million in revenue, have come back to us, Lendoe as a platform and said, 'how do we now work with these clients?'... and that's why we call them underestimated.

And we have a number of examples like that.

There are great founders out there. They're great at doing what they do, which is running their business, but what they need is someone who can actually break down all of the options that are available to them, but also someone that can give them that confidence to actually apply once they've broken down those options - because the fear of rejection, the fear of the unknown, the fear of not knowing what you're getting yourself into, is often what prevents people from going ahead and saying, 'actually, I believe I can do this'.

We have a lobster-catching business in north Wales, and it's a story about a guy who was a scuba diver in Thailand and came back to be with his family and wanted to start a lobster-catching business and needed some money for some nets and lobster pots.

And it's like, yeah, ‘people helping people’, it still hasn't really changed from that. I just think, you're gonna see projects funded that are really organic and natural.

85% of folks have bank accounts, but only about 20% of them actually use the bank (for borrowing). They rely on other forums to meet their financing needs. These guys don't have access to credit.

As a startup, when we launched back in 2018, the lending market in Sri Lanka was $5 billion - and what we understood this from this 5 billion requirement, almost 40% relied on loan sharks and individuals who have very dubious practices of charging excessive interest rates, as well as very unpleasant collection methods.

And coming from a tech and a finance background, we realised there might be a potential for us to provide credit underwriting through a blockchain solution.

We always take a very commercial and common sense attitude to everything that we're lending on: if there's a solid business story as to why they want the money; if there's a clear route to how we think they're going to pay it back; and if there's an asset that we can secure against to make sure we've got something to go after if it all goes wrong,...then for me that's 95% of the underwriting there.

As oversimplified as that may sound that really is the truth.

Because I mean, ultimately, as a lender, what more do you want than a good business that's got the ability to pay you bac

How do we let brands get in front of first party data customers with the highest intent the world has ever seen? I mean, our click to sales ratio is 55%.

Brands are paying billions in marketing budgets, so that you can see the advert you then clicking the advert getting to their site or going to their store pulling your credit card out and paying billions in interest and fees to credit card companies to buy the products.

What we've done is we've sort of said, why don't we circumvent the middleman? Why don't we let brands rather pay our customers? In other words, use the brand's marketing budget to subsidise the cost of credit to our customer, and convince our customer to buy from that brand.

The whole equation makes more sense. The customer has more sustainable buying power, because the brand is subsidising the cost of credit to the customer. So the brand can make a sale.

It's all sorts of facets of establishing a life in a new country: it's renting a property, you need a credit history to be able to rent a property. If you haven't got a UK credit history, you have to pay six months rent upfront, or find a UK guarantor. So obviously, both of those are just unpleasant experiences.

And mobile phones, we did some research recently with over 1,000, new to country people. And over two thirds want a mobile phone immediately. But again, they need to do a credit check. So they won't be able to get a contract, they'll just get paid you go or ceremony or something like that. So they'll suffer on that.

And what influenced the interest rate is really, first, the inflation and then the unemployment rate. The good news is in the US and Canada, the inflation has peaked from the six months ago, they gradually come down - inflation in the USA right now is around 6%; inflation in Canada, just above 5%. For the unemployment rate, both countries have the numbers at historically low. So good fundamentals. The interest rate hike period is probably near the end, that's the signal from the latest Fed meeting. Actually, Canada already paused once in the March meeting as well.

But obviously, we will see some credit normalizations which means the other risk metrics will go up because we saw that the early stage roll rate began to trend up. But again, when you look at the trajectory, it just goes back to three years ago, right, before the pandemic, so I think fundamentally it's still sound.

Custom Credit was really set up with three mission statements in mind - we always are asking ourselves, does this move us closer to this or further away - and that is (1) to become the most customer centric FinTech in the UK, (2) is to ensure our colleagues better reflect our customers, and (3) to improve financial literacy, both in terms of our customers and the broader community.

I think the product itself is tailored and custom. But to achieve that, the way you score and assess risk needs to be tailored and custom, that's often where the problem is with these other kind of flexible payment lenders, most lenders will make a decision on on affordability based purely on averages to estimate your your expenditure. They will use a combination of the information you've provided to them, and an indicator from the credit reference agencies.

People with very different spending profiles and very different income profiles effectively could be judged to having the same level of affordability. So we've actually taken a different approach in that, initially, all of our customers will have to provide open banking data.

What we're doing is actually really, really complicated, but you can ingest this data and then give it to the bureaus and you know, the keys format, the Insight format, depending on which Bureau it's obviously a very hard thing to build. But imagine if that real time flow of data via an API became something the bureau started to ingest direct from the API.

Step one is to simplify the integration, simplify the reciprocating of data create a common standard, but eventually I think TransUnion, Equifax, and Experian should become real time networks. You know how many customers have a buy now pay later player goes to all the other BNPL players and borrows money in the same month. And if bureau data is stale by a month, two months refreshed once a month, that doesn't get caught in the system, right?

So even though more small businesses are being formed, traditional banks are lending less to them in terms of loan volume.

And that started to get me thinking about how I might join a startup or another company that was trying to solve this problem. I looked around a lot, and I didn't see anyone that was solving in a way that I thought was really equitable.

It's funny, I talk to a lot of entrepreneurs, people that need to be their own boss ,that feel really compelled to go out and start a company. That was not me, I was a very happy cog in the wheel. I enjoyed working in corporate America, I enjoyed working in a midsize startup. And really, it was just kind of an alignment of my passions, and a problem in the industry that I saw that no one was solving a really satisfactory way. And some good mentors that pushed me into to take that leap and jump into the entrepreneurial world.