You're unifying data from different countries into one single hub, we are standardising that, we are analysing the data and presenting it to a bank's over one single API. So for a bank, it doesn't matter if the customer is coming from Poland, Germany, Spain, Italy.

Typically banks have share of foreign customers 10% to 15%. Okay, 10 to 15% is good enough to care about, but the problem is that this 10% to 15% are not coming from one single country. They are coming from the twenty seven or even more since they outside of EU like the UK, Switzerland, etc.

So quite a long list of a country - this is a problem. And it's not feasible for one single bank. They will build the data pipelines and try to build the knowledge and standardise now it's just too expensive.

But in our case, it is okay, because if we are building this infrastructure, we can sell it to different banks, and each bank is paying their share. But of course, there are plenty of hurdles not only technology hurdle, various legal hurdles. Also we have European Union one same, same legal framework, as it said, there really is in the details. So in different countries, it's still a bit different than we are solving these hurdles.

If I'm looking like 10 or 20 years back, when we were basically as a FinTech organisation the majority of our decisions were relying on the application form. So credit application form. And nowadays, it's leaning to the direction where you ask very few questions from customers. So from a UX point of view, from a customer experience point of view, it's much smoother.

And it can be super automatic - meaning by that you're able to work with a very lean organisation to support 10s of 1000s of customers. It all comes down to what kind of data sources you're able to use. So coming back to this credit application, you might have had 50 or 20 questions on a credit application 10 years ago, today, it might be that you are asking just for identification, which in countries like Finland, Sweden, Estonia, it's automatic. So basically, you're using bank IDs to do the automization.

And once the automizationis is done, then you're able to start calling different data banks, credit bureaus, all kinds of third party data banks, bank transaction history that you're also able to get through the same identification method, although it's a different call. But anyway, you are able to get so much information to support your decision making and you're able to automate the size from the beginning until the end, meaning by that in a previous life, when we were making the risk assessment, we were using application scorecards.

I had to borrow a lot of money from my peers to be able to pay my rent. Which, as you can imagine, was not a very pleasant experience. Because you have to ask, 'can you lend me a little bit of money here, a little bit of money there' and have to remember who you borrow money from.

And I was dreaming of having an application that could solve these kinds of issues for me. And back then Tinder was already popular among kids, if it can say so. But there was no Tinder-like application to just match with people for the sake of borrowing money from them. I ended up building it myself after not finding it available.

It's been four years since I started building Lendwill, and it is extremely difficult to build a good peer-to-peer lending platform that would allow individuals to borrow money from each other. So I can understand why there had not been any product that I wanted back in the day because it's really hard!