and I just said, from my perspective, as someone who used to leave her credit reports - once I finally got the courage to even request a credit report - on the counter for weeks, because I was too scared to even open it.

And what I'm hearing on the flip side is that there's just not enough education around what lending even means, or what interest rates even are, or how that affects you.

I just did a segment for Good Morning America, where I was breaking down interest rates, and they said, 'oh, we didn't know that just because interest rates go up on credit cards, it's not all bad. It also goes up at the bank, that's cool'.

So what I actually did was, I saw this potential for people who were underserved in a multitude of different ways to actually be empowered and take control of their own future through social impact businesses, which I think microfinance really comes under. And so what I started doing is leveraging my background in ERP solutions and tech platforms, and got involved in microfinance or banking tech platforms. And so it was really combining the two.

But what was really interesting was that, everywhere I went, despite the fact that countries were so different geographically and demographically, that I saw this underlying resilience and determination amongst people who just didn't have opportunities presented to them on a plate, and that given the right support, and the right tools at the right time that they could actually then forge their own futures, pretty much everywhere I was going, which was from Sierra Leone to Pakistan to Vietnam.

It's a risk, yes, but it's also a risk not to do it.

But when I started talking to other people and reaching out to other real estate platforms, there just wasn't a lot of information out there about private lending. Ironically enough, you know, Brandon Turner with BiggerPockets, his big thing was to go find a private lender to fund your deals. But then there wasn't any discussion on how to do that funding of the deal, which is why we ended up doing a book with bigger pockets, because there was that gap in the marketplace. And then also during COVID, the world shut down. You can't get together with people, you know, the RIA meetings that I had been attending, we're now posted on Zoom. But for anybody who's gone to a RIA meeting, you're not likely going to bump into somebody else who's also doing private lending. Because first off, you don't say that in public, because instantly you become the most popular person in the room and RIA meeting. So we kind of have to be a little bit of lurking happening there. But, you know, during COVID, not even that was happening. So I went out looking for community.

Yeah, absolutely. I mean, we really encourage those open discussions with our registered firms.

And in fact, we have some forums where we bring together registered and non-registered firms to discuss things like that. And I think one of the things I just want to be clear on, as a self-regulatory body (and from what I understand of regulation) is that no one really wants to stifle innovation, but I know that it can be really hard.

I think we're seeing some really good use of data and EMI and whenever we move to using algorithms to try and predict customer behaviour, etc.

The mobile wallets information I see, in a way, as a parallel option to Open Banking. It's really where somebody's having their financial transactions give us an indication of their income or their ability to spend, as well as some indication of the consistency of salary over time and the income. So I think what we've seen is combining that with the credit bureau data, you know, really provides a really strong indication of risk.

And we talked about the different data sources, some of the data sources we may not be holding within the the credit bureau, but what we're trying to do is actually facilitate so we can provide decision modules where we're bringing together that data that may be held by the telco or the bank in the mobile wallet and combining that with the credit bureau data so it's easier to use to generate those decisions for the lenders.

High level, I would say there are four elements of the lending process, and we started with one: which was how risky is it to lend Brendan a certain money? Like what's the likelihood of repayment or default, and then really allowing our lenders to specify, are they comfortable with that? How do they want to price it?

Increasingly, I think to the point you're making, we are also applying it to the second area we really focused on, how do I reduce friction in the process, right? We didn't start with this insight. This is kind of one of those you learn in the market. When we started, every borrower that our lenders were onboarding, we did a phone call, we asked for an ID to be uploaded to verify identity, that standard kind of KYC stuff that you do. And we had this insight, like, for the small loans, it costs too much money to get on the phone with people, maybe we could just use automated signals to do fraud prevention and not get on the phone, just for small loans, just for a few, to see what happens.

And so we tried it. And we saw this 2x to 3x increase in pull through and actually equal or positive credit performance. We went, 'oh, that's interesting, if I can take a certain amount of demand and turn it into twice as many loans, that's really valuable'. So we started the process of saying, can we use machine learning to get to a place where we're comfortable with more loans of larger sizes of longer durations that we can approve without that human intervention, because it both lowers the cost, but it reduces the friction.

And it turns out, consumers are not only rate sensitive on the loan side, they're also friction sensitive, they don't like putting in a lot of effort. So we are now at a place where our lenders see 70% of loans coming through the platform, having no touch origination - with ID verification, income verification done in automated ways, with very high NPS and very low cost and high conversions as a result of that.

So we can speak about Victoriabank, but first of all, it's important to understand the level of the banking system in the scale in in Moldova, because, as I mentioned, it is a small country - in terms of square meters and also in population - the GDP is around E11.5 billion, GDP per capita is E4,400, average salary is about E450 per month, with unemployment rate of 3.5% and the inflation rate, the official inflation rate, at this moment of time, it's around 22%. And to understand the banking system, it's 51% of the total GDP in Moldova. To understand the scale of that, Victoriabank in Romania alone, which is the biggest bank in Romania, is bigger than the combined banks in Moldova - but the competition is very tight and this affects the margins very, very dramatically.

There are 11 banks in Moldova, too many for this population.

Now coming back to Victoriabank, in 2018 Victoriabank was the third largest bank in Moldova. We are always proud of our history and about the innovation which were brought into Moldova by Victoriabank, since the moment it was established as a bank.

So we've created a first-world infrastructure, but it's been an uphill battle to get lenders to embrace the use of bureau data and credit scores and bureau scores to make mass decisions. In Nigeria, it's a legal requirement that you perform two credit inquiries, but that's not to say that you must make good use of the data you're given, as long as you know, you've met your legal obligations. So there hasn't really been an appreciation of how that data can help you improve your decision making. So that's the journey that I've been trying to help my clients to realise - it's been as an educational upskilling, a sort of training project as much as much as a hands-on rebuild the bureau score project.

I think one of the cultural changes that's required is the willingness to invest money in order to save money, that thinking hasn't really been that prevalent in Nigeria, in the past at least. Curiously, that's the first time I've ever encountered a situation where lenders have questioned, well, why are we paying for a credit inquiry if we ended up rejecting that customer? Why would we want to pay for that? Which kind of misses the point of the protection that screening for risk gives you.