when we are looking at new data sources, we have four acid tests that we run through.

The first is the reliability of the data - so is it from a trustworthy source? Is it compliant? Is it of good quality, all those sorts of factors. The second, as you said, is the predictive nature of the data, is it proving out or identifying the hypotheses in the insights that we expected and is doing something which existing datasets can't? The third one is about its scalability, which doesn't mean it has to be the whole population, but for the actual target audience that we're trying to benefit, does it have enough coverage? And the fourth one is, is it understandable, which I think is increasingly important for us.

And we deliberately set the bar understandable rather than explainable because they're different. My science teacher, much to his frustration, spent hours explaining the basics of physics to me, unfortunately, for me, it wasn't very understandable. But actually, that is a really that's a really important point, because it comes back to this control and transparency. If people do not understand it, then why would I trust it? So for us as organisations with new data and new insights, then we have to be able to help people understand why we're doing it and, and the inferences we're drawing.

So, about the history... actually, Russian retail lending is relatively young, it started less than 20 years ago and it made a huge jump from where we were - just basic stuff 15 years ago - to the state that we have now.

There's a positive outcome of this short history, we don't have much of the legacy technologies, etc, that some of a large international group experience that, take core banking systems, they don't have something that was developed 50 years ago, they're in a more or less modern state.

Yeah, it's definitely shifted away from what can be a very pressurised conversation where you're there, you're speaking to the agent, you're you're under pressure to share those numbers, and maybe sometimes sharing incorrect numbers because of the pressure. Some utility companies, they want evidence of certain parts of the I&E to be shared, like documentation - so our system has that.

So the patterns we're seeing are very interesting, and the journey they go through in order to share that I&E, they revisit their I&E several times before they finally share the I&E with the with the lender, you can see there might be two or three times they're going back and forth to the I&E. They're updating it on our system, doing it in their own time. And then right at the end, maybe after a day, or two or maybe a couple of hours, they then share their I&E so it's a much more fulfilled I&E to then have that conversation with the agents as I said, it's a more mature to conversation. Obviously they share that I&E then with all lenders as part of building that I&E network, which is what we're here to do.

Another indicator that is significant is that BNPL meant around 3% to 4% of the total e-commerce sales in Spain, while in Sweden it is around 20%. So we see significant growth expectations for the years to come.

Then also remember that if I'm a merchant and my aim is to maximise my sales, and suddenly I have to talk to five different lenders, or negotiate with them, I may not have the skills nor the time, to do it. Well, we do that for you. So you just have to focus on what you best know, which is selling through your, your webpage, and we take care of the rest.

And what we shouldn't forget is that, you know, the banks don't want fraud to occur. They don't go looking for that. And they're spending huge amounts of money to defend and protect against it. And trying to balance that with making sure that the service they provide to customers is convenient and easy because you just talked about the frustration of being stopped from getting access to something when that happens, they don't want to inconvenience you, or they also don't want you to be a victim of fraud. We shouldn't forget. And it sounds like I'm a massive supporter of banks, and I am to some degree, but I often read articles and I think the article is completely ignoring the fact behind all of this there's a bad guy, there's a fraudster who's gone out and committed fraud, committed deception. They've taken money out of that, or whatever it might be, the bank didn't ask for that don't want that. I'm just trying to protect against it.

Well, let me paint a picture of the banking landscape at that time, the banking landscape in the 90s in Ghana, West Africa, we were just beginning to wake up to the advantages that digitization could bring in terms of transforming from manual processes to technology-based processes. And more of automating the manual process, rather than looking at the processes end-to-end and transforming them. Very, very basic accounting, very basic bookkeeping, and all of that.

And nothing really digital as we know it today, because still if you wanted a banking service, you had to go to the bank physically, all that really had to change was that we're able to do a lot of transactions in a shorter period of time. And our books were more accurate.

But by the mid-1990s, I had started getting a little adventurous with what we could do with the technology stack that we had.

… one of the reasons that immigration is so essential to the US economy and to the US labour force is that our domestic population is not replenishing, our birth rate in this country is no longer outpacing the demographic shift as the older generation exits the labour force. And what that means in terms of US population growth is that today, immigration drives over 50% of the US population growth...

There are more people today that move to the US than there are people who turn 18 and enter the financial system… and so not having a dedicated strategy for how to attract and retain the recent immigrant segment is a formula to demographically lose market share over time.

"The risk of giving into temptation is as old as humanity. But there are reasons to think that people today are having to work harder to resist it, particularly when it comes to consumer behaviour. Digital technology has made it easier and faster to buy goods and services in an instant, without the delays of processing that once comprised an inbuilt cooling off period". This might sound like a headline from today's papers, but in fact it was from an article in The Financial Times published seven years ago, almost to the day - at a time when Klarna was around, yes, but only just beginning its global expansion, Affirm was only two years old, and AfterPay only a few months old. Welcome back to How to Lend Money to Strangers, the podcast about consumer lending strategies across the credit lifecycle and around the world.

Yeah, it was about helping a friend to get on the property ladder. She's done very well in her career now, but at that point, she needed some help. And she was like, I really want to stay in my local community, and I really want to buy with my husband here. And she just asked us on WhatsApp if we'd lend, but it was just a lot of money to a group of people at that time. And it was like, how are we going to get paid back because we were all recently graduated. So although that loan didn't happen, that's kind of what inspired the idea for JustLend. I wanted to provide opportunities to people could do what they wish to do.

There's a whole bunch of people out there where the traditional model doesn't work, there simply isn't enough information on these people to make a reasonable credit call...

This is a space where lots of people are working, but very few people can claim results. Because this is also the sort of space where lots of AI propellerheads think they can crack the problem. To some extent, that's true. This is also the classic case where progress is both hindered and aided with experience. It's actually good that some youngster on a beanbag, with long hair, thinks about this stuff completely unhindered by any previous industry knowledge, because that's anyone with too much experience probably thinks too much inside the box. At the same time, with something like credit, you do need to have some other people in there who can say, 'well, yeah, that's cool but you need to take these following five things in'.

That doesn't mean that the thinking needs to be restrained, but someone needs to make it practical in the end. To simply let the same space cadets go mad on this is likely to land you in a heap of problems, if you don't actually understand the lending industry.

So that was my focus point is, if you've got nothing, that's where we start… for existing clients, you can just go with the Chief Operating Officer to a branch, have your scoring, talk to the loan officers about the clients, they know them, right, you'd be surprised by how many they have but they know them by name, and test the scoring.

It's not the only that the banks won't give the card to them, because they are too young, they don't have enough income, or things like that, they just don't want to go through the more tedious process to get a credit card… now you don't need to go to any banks, you don't need to produce any documents, and you can get a loan in maybe a couple of seconds.

We are always on the lookout for new data sources, or external providers, and whenever we see something that's interesting, we test it… In the end, it comes down to what can we pay per gini point of lift?

You have to operate in the realms of the known and not in the realms of ‘well, we think this happened’. And that's why you absolutely have to have a champion/ challenger strategy, as difficult as it may be.

The common feature here was that, like banks were slow to be on the take up of the scoring methodologies, FICO was slow to see the value of bureau information. And for that matter, the credit bureau saw FICO as a competitor, they didn't see FICO as somebody that they could collaborate with. And yet nowadays, a FICO score is synonymous with a bureau score.