It's still dominated by your credit card issuers.

So most people if they have Apple Pay or Google Pay, they have loaded their credit card and that's probably the most popular form of payments, but these QR payment providers who have their own mobile apps is very, very popular. And it's accepted everywhere. And while they still represent a very small share in terms of total purchase volumes, they are by far the fastest growing, and that is why issuers are very, very concerned.

And these QR payment providers are also going into that credit space, where they're offering a small credit of maybe $500 to $1,000. But they're using very basic information - just your name, phone number, email - so it's much, much faster and easier to apply for that new QR payment credit versus a traditional credit card.

And I actually want to take a step back here, if you don't mind, and just make a few remarks about people in Alif overall, about about our efforts in combining technology and education. I don't know if you if you knew this, but the average age of our employees is 25. We have a lot of students, recent graduates. We train them ourselves. So to give an example of specific training, IT skills is an area where we felt that we could contribute to the education system in Tajikistan. So we established Alif Academy in 2017, as a nonprofit where we promote it education. So we provide free programming courses, including special courses for girls, for kids, for Afghan refugees.

So far, we've had more than 2,000 graduates of these courses, and some of them working, at least some of them work in other companies. And hopefully now in the new countries we had, and we have the privilege of being able to attract some of the most bright, kind, noble, energetic individuals throughout all these years, we had more than 50,000 applications to to our vacancies. And we've chosen and retained the very best.

If you have to remember what we talked machine learning AI today is not something that's come around today, right? What has changed today is our ability to store enormous amount of data economically. Number two is the processing speeds we have today. You know, you want a search bar before you type, your third word is already telling you what it should be. So think about it. And there are millions of people doing it at the same time, any second. And the third thing is the speed of transmission of information.

I think those three in combination literally are the most fertile ground to bring AI to life.

And that's what we've essentially done. But be mindful that when you're doing things at that speed, there are things that could happen which go out of your control.

Because again, credit scores really don't resonate well for that customer, but the fact that I can access more loans and more services from the bank makes a lot of sense, right?

So, the messaging itself can we change, make it more people friendly, make it more empathetic, again, is is an important factor that we keep working on. So understand the behaviour the formats, the messaging, and then devise and develop a complete strategy around customer engagement, what is the life cycle that we can build? So segment and perhaps micro segment the customer and build optimised life cycles for these micro segments of customers that we are onboarding and all that is to ensure that these people understand their loans make their payments on time?

There shouldn't be any instance where you know we have to limit the access to the device. So the idea is never to reach that hence, how do we use AI and ML to create very effective and efficient life cycles, messaging journeys for these people. So that, you know, the delinquencies are in check.

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.