The Connector Podcast - Pivoting to Success: How POM Transformed Invoice Payments and Mastered the Fintech Space
May 02, 2024Season 1Episode 48
Koen Vanderhoydonk (The Connector)
Ever wondered how a simple pivot can redefine a company's destiny? That's exactly what Johannes from POM reveals as we explore the transformation of the invoice payment landscape on the Connector Podcast. Johannes takes us through the inception of POM, originally designed to ease the pain points of consumers managing their bills, to its strategic shift in 2017 which now serves the needs of businesses for expedited and accurate invoicing. This episode is a goldmine for anyone interested in the evolution of a fintech startup and the innovative solutions that come from persistence and adaptability.
Join us as we converse about POM's current achievements, boasting around 2,500 customers, and their expansion across essential sectors. We also scrutinize the integration of artificial intelligence in POM's services and their recent partnership with Mail2Pay, which has been a game-changer since December 2022. This discussion is not just about fintech innovation; it's about how a company like POM is carving a niche in revolutionizing business transactions for happier customers and healthier bottom lines. Tune in for an inspiring journey through entrepreneurship, technology, and the power of a well-timed pivot.
Thank you for tuning into our podcast about global trends in the FinTech industry. Check out our podcast channel. Learn more about The Connector. Follow us on LinkedIn.
Ever wondered how a simple pivot can redefine a company's destiny? That's exactly what Johannes from POM reveals as we explore the transformation of the invoice payment landscape on the Connector Podcast. Johannes takes us through the inception of POM, originally designed to ease the pain points of consumers managing their bills, to its strategic shift in 2017 which now serves the needs of businesses for expedited and accurate invoicing. This episode is a goldmine for anyone interested in the evolution of a fintech startup and the innovative solutions that come from persistence and adaptability.
Join us as we converse about POM's current achievements, boasting around 2,500 customers, and their expansion across essential sectors. We also scrutinize the integration of artificial intelligence in POM's services and their recent partnership with Mail2Pay, which has been a game-changer since December 2022. This discussion is not just about fintech innovation; it's about how a company like POM is carving a niche in revolutionizing business transactions for happier customers and healthier bottom lines. Tune in for an inspiring journey through entrepreneurship, technology, and the power of a well-timed pivot.
Thank you for tuning into our podcast about global trends in the FinTech industry. Check out our podcast channel. Learn more about The Connector. Follow us on LinkedIn.
Welcome to the Connector Podcast, an ongoing conversation connecting fintechs, banks and regulators worldwide. Join CEO and founder Cohen van der Hooydonk as you learn more about the latest available trends and solutions in the markets.
Speaker 2:
Welcome to another podcast, fintech Belgium and the Connected together. And today I've got Pom. Johannes, can you please tell me what is Pom? Well, hi, koen.
Speaker 3:
Nice to be here and nice to be invited by you, and nice to be in this splendid location here of Fintech Belgium.
Speaker 3:
Absolutely A few years ago, it's like in 2014, we started with the company Pom and he is Tom Totten and myself, tom Totti, my co-founder and we started with POM, and POM stands for peace of mind, and our big idea at that time was creating peace of mind for people in the whole invoice payment process. And what we did is actually, we had a splendid idea. We wanted to make an app that allowed you to receive your invoices, pay them with one click on the moment they had to be paid, to store them automatically and then share them automatically with whoever needs them, like your accountant or your wife or your husband or whatever. And although it was a splendid idea, and although we worked it out also very nicely, we found out after a few years that convincing a consumer market in downloading your app at the first place and then continue using it it costs you a lot of effort and, especially, a lot of money. And what made us make our big pivot and we made a big pivot in 2017- like many of the startups do.
Speaker 3:
Yeah, yeah, I think. Yeah, if you haven't done a pivot, you're not a startup. I would say so. We did a big pivot as well. Uh, somewhere in 2017 then, and we thought, well, instead of going to the consumer and trying to convince the consumer to use our app, and then by having a lot of app users also trying to convince the businesses, why don't we go directly to the businesses? And that's what we did. And then we told them we can help you getting your invoices faster paid. Oh, and that sounds nice and that was nice, and it struck an interest, and we were lucky to well have as one of our first customers one of the biggest energy companies in Belgium, and that kicked off all the rest. So, yeah, what we did is what we did, and what we do now is that we add payment tools on invoices, and the payment tool can be a QR code and a paper invoice, can be a pay link and an email or an SMS or a WhatsApp message, and it allows you just to pay easier.
Speaker 2:
Which for the companies is really nice because they get the money obviously sooner, I guess, yeah.
Speaker 3:
So they get the money sooner. They get the money always 100% correct, so the message is always correct, the amount is always correct, so there's 100% automatic reconciliation of all the payments that come in, and they have happier customers Because, okay, yeah, who doesn't like to just click and pay instead of having to type over all this boring stuff every month again? And based on that, yeah, we grew to now we have about 2,500 customers in all kinds of sectors. We work for the government, we work for major energy companies, utility companies, lots of hospitals, lots of schools, lots of sports clubs, lots of small companies as well, so every company working actually towards customers. And so we have B2C companies as customers.
Speaker 2:
Well, Johannes, thank you very much for sharing this story with us. It's a great startup story. Now in our preparations, we said we also talk about AI. But now I'm wondering with such a solution, do you really need ai?
Speaker 3:
uh, well, it's an intelligent solution on itself already, but anyway, maybe to complete the story and then, and then you'll see the ai coming in. Um, actually, we, we became part of a group. The group was called at that time Mail2Pay, back in December 2022, and Mail2Pay was actually specialized in credit management, the creation and follow up of invoices, outgoing invoices, and it was we said at that time, and we continue to say, that it was a match made in heaven. And so we have no uh, we put the joint product in the market, uh, since, uh, since December 22. Um, and and actually, it is in that product that we actually use AI.
Speaker 3:
And well, ai that we use actually, well, it was already invented before the word AI was actually trending and at the time, we still called it machine learning. But what we actually do is, first of all, we give peace of mind also in, well, the distribution of invoices and the follow-up of invoices. That's why we have this match made in heaven with mail-to-pay group um, but what I actually do is something and we call machine learning. So we, we developed a um. It's like five years ago, we developed um, a model um that actually will help you or will decide in your place about the best moment and the best channel to connect to your customer in order to get your invoice paid.
Speaker 3:
And I must say it was at that time it was very, I would say, forward-looking and innovative. And so we created a model, we trained it. We had like a million records, we trained it with 700,000 records and then we tested it afterwards with the other 300,000 records. And actually the model does two things.
Speaker 3:
It will, first of all, based on your age, the region where you live, your age, the region where you live will define, will try to calculate how big the chance will be that you will respond to a communication via different channels and on different times and based on that, we'll make a prioritization. And, based on the group you're in, it will prioritize. For instance, it'll say, okay, we haven't paid your invoice. You will get your next reminder via SMS because your group, your region, reacts best on that. But that kind of information, we will also match them with the record of that specific person and say, okay, we know your history. We've sent you a lot of SMSes already previously and never responded on it. So, although it is best for your group, it is probably still better to send you know a letter or an email and based on that, the system decides when and through which channel the communication is sent.
Speaker 2:
So actually you're talking about a very far-fledged personalization. Yeah, so clearly an opportunity on AI, but I was wondering what would you see as challenges specifically done in this whole payment sector? If I may, challenges I would.
Speaker 3:
I would have to say there's more opportunities and basic thinking. What we have is that AI, well, should not replace humans, should never replace humans, should support humans. And a very nice example. And it just happened to me like yesterday night I did a transaction. It didn't went through. Today I wanted to pay with my credit card and it was blocked.
Speaker 3:
But actually I received an SMS that said, okay, well, we found a suspicious transaction, please call to this number and you have a code here to skip the line. And actually I was received immediately. So I phoned Immediately. I got somebody on the phone and I said, yeah, well, we think that transaction that you tried to do, or that was tried to be done yesterday was suspicious and it blocked my card and and the transaction was blocked then and but I had a very good conversation with that person and, okay, we could explain everything and the card was re-blocked. So, and I think this is a very big opportunity I see in ai, ai will become better and better in finding suspicious transactions. Doing an action on that, yes, but in Finney, it's finally the person that actually it's a human person that will interpret and will finally take the decision.
Speaker 2:
Yeah, so I think we're talking more about augmentation of processes then.
Speaker 3:
Absolutely. I definitely think about augmentation and I don't see us in the near and maybe even the further future not really being replaced by robots or artificial intelligence.
Speaker 2:
I see us being helped a lot by artificial intelligence and I would think, in this sort of way of thinking, that we would be helped augmented. Do you still believe there is ethical concerns in this whole realms of ai? Then?
Speaker 3:
there is that ethical concerns if, if, if you, if you don't put the human in the front and if you think that, for instance, your salesperson or your support person is going to be replaced by an ai because the ai does it faster, then you're wrong. I think ai, as good as it is now and can be and will improve, it can still not replace a human person, but it can absolutely improve a lot of service you can give and it can help you getting rid of the boring task like responding to a mail. It can prepare a mail for you but you're going to read it and you're going to finally send it through and maybe change your ender sentence, but it helps you with the boring stuff, eliminating the boring stuff. A second thing it can absolutely help you enormously. It's of course. It can process lots and tons and tons of data and much faster than we have. So it can help you getting the insight you need to offer a better service, but it always comes back to the human.
Speaker 2:
I think it is a supporting tool so how does pump stay ahead in terms of adopting two new technologies and and make sure that you're sort of in the forefront of global payment systems?
Speaker 3:
yeah, yes, first of all, of course, we keep our eyes open, but I mean, you would be, uh, not a good company and not leading Well your company if you don't do it. We keep our eyes open. We have set up a team as well that is working around AI and evaluating the opportunities around AI, other than, of course, what we're already doing with machine learning. But what we want to do we don't necessarily want to be the front runner. We process millions of transactions, even on a monthly basis, and it has to go fluently, and you can't accept even 0.1% of errors there, because otherwise that adds up to thousands of errors in a month. So what we do? We do tests, we see what's in. Of course, we follow up the market. We will only release things of which we're 100% sure that it's going to work.
Speaker 2:
So it almost sounds like an infrastructure.
Speaker 3:
Yeah, absolutely. Again, we have our laps on one side, but before something comes from the lap into the actual system, it really needs to be 100% proven.
Speaker 2:
Makes sense. We're almost at the end of our podcast conversation. I was wondering who should contact you and how should they contact you.
Speaker 3:
I'm eager to talk to everybody who's interested in hearing more about what we're doing, and so if you want to have a conversation with me, just send me a message through LinkedIn and I promise you I'll answer, and if you find an interesting topic, we'll certainly are going to sit together.
Speaker 2:
So also philosophy, definitely. Thank you very much for having you here in the podcast. It was a pleasure. Thank you also for the audience for tuning in and stay tuned. More news from the financial industry, thank you so much. Thank you very much for having me here. You're welcome.
Speaker 1:
Thanks for listening to another episode of the Connector podcast. To connect and keep up to date with all the latest, head over to wwwjointhekonnectorcom or hit subscribe via your podcast streaming platform.
