Why 98% of B2B Payments Still Fail at the Human Level

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Welcome to FinTech Confidential, bringing you the

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people, tech and companies that change how you pay and get paid.

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98% of B2B payments are still done manually $70 trillion B2B payments market

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Major Rideshare companies employing 50 plus person accounts receivable

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teams.

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it's seen as the most unglamorous, most boring corner of FinTech

Duncan Barrigan: 00:00:27

honestly, I was just sat on the sofa one day and the whole

Duncan Barrigan: 00:00:29

thing just came to me like that.

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if you don't embrace the chaos, you're not gonna be able to handle it.

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the thing with problems like this is they just draw you straight back in,

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AI agents don't just automate payments.

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They negotiate, communicate,

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and resolve disputes just like humans

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it's possible that we end up in a fully autonomous AI negotiation

Duncan Barrigan: 00:00:48

Why for thousands of years people have done it the same way,

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we found out it was natively multilingual

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I'm human.

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I make mistakes.

Duncan Barrigan: 00:00:55

We all are, we all, we all, we all make mistakes.

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think about how the human would do and then imagine how you could make

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it superhuman.

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Focus on solving the customer's problem as best as you can and let

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everything else take care of itself.

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Hey, Tedd Huff here.

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Welcome to FinTech Confidential series leaders one-on-one, where we sit

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down with FinTech leaders to learn about what drives their passion for

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FinTech, for their business and their leadership lessons i'm your host,

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Tedd Huff, and today's guest is Duncan Barrigan founder and CEO at Lunos.ai

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Duncan, welcome to the show.

Duncan Barrigan: 00:01:57

Thanks for having me, Tedd.

Duncan Barrigan: 00:01:58

Great to see you.

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If you don't know who Duncan is, no big deal.

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But Duncan, he left a $2.2 billion unicorn to solve what he calls the most

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boring problem in business, but one that is worth over $70 trillion annually.

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After scaling GoCardless to processing over a hundred million dollars in

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annual recurring revenue, Duncan discovered a shocking reality.

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98% of B2B payments are still done manually with companies like Major

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Rideshare companies employing 50 plus person accounts receivable teams.

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His hammer and nail awakening led to founding Lunos AI in 2024.

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Where AI agents don't just automate payments.

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They negotiate, communicate, and resolve disputes just like humans,

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but never get tired, never forget, and they actually scale infinitely.

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just a few weeks ago I had this invoice nightmare dispute that really proves

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the point that Duncan has made in my conversations with him, this client.

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Missed paying one invoice.

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It seemed pretty simple, but then I sent the follow up email saying, Hey, did

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you accidentally forget to pay this?

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He fired back with an email and says, yes, I have paid this, and then rattled

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off a whole bunch of conflicting details, and we were going crazy with this one,

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and then of course, I had to make it worse because I didn't export out of the

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accounting system and sent it to him.

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Which had all the wrong data in it too.

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this forced me to download three months of bank statements, cross-reference

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every invoice I'd ever sent.

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Compare that to what was marked as paid in the accounting system, and spend an

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hour and a half on the call with the client walking them through line by line.

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All because they questioned whether I even knew what the heck I was doing.

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I'm a payments professional.

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And they were questioning that.

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That's exactly the communication chaos costing businesses millions

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and millions in operational overhead.

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And that's exactly what Duncan realized.

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It isn't a workflow problem, it's really a communication crisis.

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So, Duncan, what do you think of the chaos I created?

Duncan Barrigan: 00:04:08

It is a fabulous example.

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I should say you're not alone.

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The stories I hear are, are crazy, but yours is, it is a pretty good one.

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So for our audience, you were the Chief Chief

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Growth Officer at GoCardless.

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At the time, it was valued at $2.2 billion and over a hundred million dollars a RR.

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most people, I mean, they like, heck, I would've even killed for that position.

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But you decided to walk away and tackle accounts receivable.

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Literally, as you said, it's seen as the most unglamorous, most boring

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corner of FinTech from the outside it sounds like career suicide,

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but how did you discover that?

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$70 trillion B2B payments market and decided to change everything.

Duncan Barrigan: 00:04:54

for me, it was a bit of a hammer and nail moment.

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I had spent all that time, so I was chief product officer as well, and

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had spent so much time thinking about how to help businesses get paid.

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when you hold a hammer that is pulling money from people's bank

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account, you tend to think that the answer is always, in fact, to pull

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money from people's bank account.

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And then when I put my hammer down, I suddenly started thinking, a

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bit less biased about the problem, that's when Lunos came to me.

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every entrepreneur and every founder has that, that light bulb moment

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when you realized you had to do this what was that specific moment you realized

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it had been done fundamentally wrong?

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When did you put down the hammer, as you said.

Duncan Barrigan: 00:05:34

I first left GoCardless and took some time

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off to figure out what to do.

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I'd always wanted to do something and I thought if I keep riding this

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rocket ship, I'm never gonna do it.

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So I sort of forced myself to leave and figure it out.

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I spent a while trying to do something completely different.

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the thing with problems like this is they just draw you straight back in,

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honestly, I was just on the sofa one day and the whole thing came to me like that.

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in my head I was like, that's what I'm gonna do.

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how did walking away from being the chief growth

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officer at a $2.2 billion unicorn.

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how did you get the mental clarity to see what other payments companies

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and other AR companies were missing?

Duncan Barrigan: 00:06:12

stepping away and reflecting, I'd always wanted to start

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something I'm a person that does things very full throttle, and therefore I

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think it's quite hard to have those moments of reflection when I'm going,

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as hard as I can Taking that time out to think about it, allowed me to connect

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the dots in my head and say, hold on.

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I've been going about this wrong all along.

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it was kind of, a matrix moment where it just came together in my head

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from that point it's been very clear ever since that I'd been looking

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at the problem wrong I had been.

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Looking for answers that I wanted rather than really trying to understand as

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deeply as possible what was, going on and why are these 50 plus person AR teams?

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You know, I hadn't, I hadn't really stopped to ask that.

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this is a very important topic to me personally, because not

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only do I run multiple companies, but in my career I've built

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custom ar AP solutions for both.

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Complex B2B as well as B2C as well as B2B2C.

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they have 60 plus person reconciliation teams and some of the software that

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we've had to build was like one piece of software, incoming payment reconciliation.

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Then another piece for outgoing payment reconciliation, and a third system too.

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do paper check payments, and then electronic payments, and then manage

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collecting or receiving funds.

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we're talking about payment dependencies where you.

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Can't pay an invoice until you receive invoice B. But then the amount

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gets applied, depends on what was paid and whether it was net seven,

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net 15, net 30, net 60, net 90.

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And then of course, you've got all these fun things where rebates

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start to sit on top of everything and adjust all these fun things.

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it really feels like every off the shelf workflow solution seems

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to break the moment this kind of complexity hits, You've seen to

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figure out how to solve for the most unpredictable factor in all of this.

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human chaos of a disputed payment or negotiation.

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that sounds impossible until you see it work.

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can you tell me about that first beta customer?

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That completely broke all of your assumptions.

Duncan Barrigan: 00:08:23

our approach from the beginning when the core

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realization I had was, well, this way that humans have been handling B2B

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payments for essentially all time.

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It's been there for a reason.

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we've shifted now people use emails and spreadsheets and PDFs.

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I guess at first it was stone tablets and messenger boys and carrier pigeons.

Duncan Barrigan: 00:08:43

Right.

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But the, the whole thing was the

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I mean, you could go back to Mesopotamia where they

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were doing ledgers on clay tablets.

Duncan Barrigan: 00:08:50

Exactly, so, so as far as I know, one day I'll write,

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the history of how, invoicing has been done, technologies have changed, You've

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still had the same process, which is.

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to say, you've got this human that sits here and looks at every

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single customer and tries to figure out what to do with them.

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as you said, this is a communication and negotiation problem rather

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than a payments problem.

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So, we went away and we built the agent to act like the human did,

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that's before you account for the madness of what actually happens

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when humans start responding to it.

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you had mentioned to me, that there was one customer email that

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made you question more specifically your beta testing assumptions.

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And.

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Forced you to redesign your approach to handling this real world

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invoice chaos as you're describing.

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Walk me through what that was like and what was going on in the

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team's mind when all this happened.

Duncan Barrigan: 00:09:46

the very first reply we ever received.

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Appropriately enough.

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I think, I think I'd even asked some of our advisors, how often is it that

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people respond in more complex ways?

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they're like, yeah, it's relatively common, but you're probably okay.

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You can start with a simplistic set.

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we'd assumed that there would be one reaction per email.

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the first email comes in and about three of us, sort of huddled around on, on Zoom,

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looking at this email, it takes us about.

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Five to 10 minutes between us to understand what the email said.

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It was along the lines of, in response to your email from Lunos, the AI

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in response to your email about my four invoices, invoice number one.

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I sent the check you haven't cashed it in response to invoice number two.

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I don't think that balance is right.

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Then referenced invoice number five, which didn't exist.

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and said something else about invoice number three and four.

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all the references were slightly mismatched.

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It was just one of those moments, especially for the engineers

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involved, where they suddenly like deeply realized the problem.

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'cause they spent 10 minutes trying to read a single email and interpret

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it at that point, we obviously had to think, had to think a bit differently,

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we chose to make the product much more agentic than we previously thought,

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because this, this just doesn't work.

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To have such sort of trying to be so defined about it, you actually have

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to, you have to embrace the chaos.

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if you don't embrace the chaos, you're not gonna be able to handle it.

Duncan Barrigan: 00:11:04

So now Lunos, the AI is a chaos embracing agent

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how do you structure the AI to actually make decisions about escalation?

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When does it route to customer success manager versus an AP manager versus A

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CFO, and how does it learn those patterns?

Duncan Barrigan: 00:11:23

the way I think about this problem is that.

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There is quite a defined list of things that could happen.

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It's just that the combinations and permutations kill you.

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there might only be, in theory, like 20, 25 different elements of a response that

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someone could give to an email and three ways you might respond to each of them.

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But they can happen in any combination across any series of emails, and The

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reason this is completely unsolvable without ai and why for thousands of

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years people have done it the same way, is because there's literally billions of

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combinations of what could happen in this, and you just can't encode it in any way.

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So the

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way we've approached it really is to blend.

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The building blocks that you can to bring the reliability and

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standardization to each piece with the agen approach to be able to handle

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every which way they come at you.

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it's a combination of how you can bring reliability and structured data.

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That is very domain specific.

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then combine that with, the latest models that allow you to

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have an agent to go about it.

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So I think it's always that combination of the structure you

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bring and the, uncertainty and agent nature that you can combine with it.

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we are always seeking the right balance so that it can cope with in a heartbeat.

Duncan Barrigan: 00:12:38

we had one the other day where, we found out it was natively multilingual.

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someone responded in German.

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the customer that was telling me about this said, a bit worried for a minute.

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I had this email in German, there's a little wizard that you

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can see for replies when you've not let it do it automatically.

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they clicked through it and they're like, you know, it's converted it.

Duncan Barrigan: 00:12:55

They're making a payment promise, I think it was.

Duncan Barrigan: 00:12:58

then the reply, it, uh, it had written it.

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In German, for the customer, and half in English underneath for him,

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so that it actually had the email in both languages and we had no

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idea it could do this, to be honest.

Duncan Barrigan: 00:13:10

It's just, it's sort of an emergent, effect of the agent.

Tedd Huff: 00:13:13

You gotta love undocumented features like that.

Duncan Barrigan: 00:13:17

Yeah, exactly.

Duncan Barrigan: 00:13:18

Exactly.

Duncan Barrigan: 00:13:19

yeah, it's that combination of the structure you bring and the

Duncan Barrigan: 00:13:23

chaos that you embrace to handle the way that humans really act.

Tedd Huff: 00:13:26

I think it's interesting, the way you're describing this, reminds me

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of when I had a conversation with, Dave Glazer, the CEO of Dwolla, and he was

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talking about how they leverage AI in their organization they have this theory

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of, above the line and below the line.

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you do as much above the line with AI and machine learning

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And when you can't automate it, when it requires human intervention, that's

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when you start to bring that in.

Tedd Huff: 00:13:53

it sounds like that's kind of the way that you've approached this, especially

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going from an email first architecture.

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why was email the first place you wanted to start?

Duncan Barrigan: 00:14:03

Email is the base layer that allows everything else, if you start

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saying to people, you are going to have to log in this way, or enter the information

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in that way, then you can no longer be The network of agents that can power B2B

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commerce, you're never going to persuade everyone to do any of these things.

Duncan Barrigan: 00:14:21

it is in fact, our customers and, prospects are annoyed at the people

Duncan Barrigan: 00:14:24

on the AP side that are creating all of these barriers, So for me, email.

Duncan Barrigan: 00:14:28

Embraces the human nature of the problem and allows you to fall

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back whenever there's nothing else.

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You don't actually need an API, you can just email them.

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And the API becomes a nice to have for a more efficient way of communicating

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email is the bedrock of the world's a p ar system, and we wanted to be natively

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built on that with everything else and extension, rather than saying like.

Duncan Barrigan: 00:14:50

If this only works in certain ways.

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Otherwise, you're straight back at, me with my hammer saying the answer

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is that you log into a portal.

Duncan Barrigan: 00:14:56

No, this is the, the humans are right.

Duncan Barrigan: 00:14:58

We are just trying to make a scalable and optimizable version of the humans

Tedd Huff: 00:15:01

I've personally seen teams manually tracking payment promises

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and, and slack channels, right?

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reconciliation processes that are taking weeks instead of hours.

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ACH rejects that trigger a whole cascading.

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Level of manual workflows where the chief operations officers or the chief

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financial officer have to immediately jump into a Slack channel as soon as

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there's a customer response, and then they can figure out how to fix the automated

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Dunning sequence and, work through that.

Tedd Huff: 00:15:33

I personally have built workflows with AWS, N8N, make.com and

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other custom solutions too, but.

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the moment a human responds to an automated email, it seems like everything

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breaks and becomes manual again.

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one of the things you guys are focused on is making the AR departments

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more efficient with AI while actually improving their results.

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So I wanna have specific numbers some specific measurable, like workforce

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transformation, cashflow, acceleration, numbers that like that customers

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are reporting with real ROI Data.

Duncan Barrigan: 00:16:11

think of monitor, suggest, and act as the three

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modes of Lunos that you can use for each individual customer.

Duncan Barrigan: 00:16:18

So monitor, you just leave everything as you are, but you, there's no ai, but you

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see a single pane of glass suggest makes.

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It.

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Lunos's problem, not your problem, but you still have to approve everything.

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And act is where the real magic is, like you've handed it off to a junior worker

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and off it goes and it'll come back to you when it needs things, but it's off.

Duncan Barrigan: 00:16:36

so one of the customers.

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were ready to shift to act mode.

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within the first, two days, a quarter of the entire AR balance

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had been paid because no one ever gets to even on suggest mode.

Duncan Barrigan: 00:16:47

No one actually

Tedd Huff: 00:16:48

Whoa.

Duncan Barrigan: 00:16:48

gets to all of these.

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They end with all these actions and then they unleashed suddenly.

Duncan Barrigan: 00:16:51

Here you go.

Duncan Barrigan: 00:16:52

I think it was nearly a million dollars.

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that came in, within a couple of days.

Duncan Barrigan: 00:16:55

So, you know, the, the

Tedd Huff: 00:16:57

Wow.

Duncan Barrigan: 00:16:57

of the, the scale that you can do is really quite

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significant, when everyone I ever meet is doing this with a spreadsheet,

Duncan Barrigan: 00:17:04

there's only so many emails you can send and store in your spreadsheet.

Duncan Barrigan: 00:17:07

Whereas when you know that it's all gonna be recorded for you, or the invoice

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issues that can kind of come back and you're not gonna have to record them.

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you can have that confidence to, to actually act more.

Duncan Barrigan: 00:17:16

the effect can be pretty dramatic

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Tedd Huff: 00:18:21

you're talking about, those three stages and the act side of the house, I had to

Tedd Huff: 00:18:26

go back to my ACH reject nightmares, walk me through how Lunos, handles this type

Tedd Huff: 00:18:33

of reject nightmare from becoming just a notification, but more of a resolution.

Duncan Barrigan: 00:18:41

the first step is, we are pro replying, not no reply.

Duncan Barrigan: 00:18:44

we really embrace and encourage people to come back with these questions

Duncan Barrigan: 00:18:48

because if they just sit there and ignore your emails and ignore your texts.

Duncan Barrigan: 00:18:51

you don't really help.

Duncan Barrigan: 00:18:52

when they come, what's really happening is, interpreting the message figuring

Duncan Barrigan: 00:18:57

out what records need updating Drafting the reply and then changing everything

Duncan Barrigan: 00:19:01

else in response, if someone comes in with a dispute for the first time,

Duncan Barrigan: 00:19:05

it should be identifying that this is a dispute, it should be, identifying

Duncan Barrigan: 00:19:10

which invoices this is in Question.

Duncan Barrigan: 00:19:11

Was it all of them?

Duncan Barrigan: 00:19:12

the core problem.

Duncan Barrigan: 00:19:13

This is why actually kind of in some regards, one of the magical stages

Duncan Barrigan: 00:19:16

is keeping the records up to date.

Duncan Barrigan: 00:19:18

essentially everyone we meet has some kind of spreadsheet that they download

Duncan Barrigan: 00:19:22

ERP once a week or probably less half the time, They're trying to sort of

Duncan Barrigan: 00:19:26

mark which ones are, are done, and they're trying to keep track of what's

Duncan Barrigan: 00:19:30

reconciled and what's not and all this.

Duncan Barrigan: 00:19:32

but when your records go wrong, the simple version of your story

Duncan Barrigan: 00:19:34

is avoided because the records aren't wrong in the first place.

Duncan Barrigan: 00:19:37

So you don't even deal with the question.

Tedd Huff: 00:19:40

Well, if I would've downloaded their files it probably would've made

Tedd Huff: 00:19:44

it a little bit easier on myself.

Tedd Huff: 00:19:46

But,

Duncan Barrigan: 00:19:47

Yeah.

Tedd Huff: 00:19:48

I'm human.

Tedd Huff: 00:19:48

I make mistakes.

Duncan Barrigan: 00:19:50

We all are, we all, we all, we all make mistakes.

Duncan Barrigan: 00:19:52

that's the classic aftermath that we see all the time, it's exactly that

Duncan Barrigan: 00:19:56

combination of like, how, how good were the records in the first place?

Duncan Barrigan: 00:19:59

Did you keep 'em up to date?

Duncan Barrigan: 00:20:00

And then.

Duncan Barrigan: 00:20:01

How quickly and reliably can you respond to what's happening.

Duncan Barrigan: 00:20:05

we would've marked the invoices done.

Duncan Barrigan: 00:20:06

with an issue, we would start investigating it.

Duncan Barrigan: 00:20:09

It would prevent any further action against the person in the meantime.

Duncan Barrigan: 00:20:13

Lunos would be bugging you about the fact that you haven't resolved this yet.

Duncan Barrigan: 00:20:16

the key part really, about your example and the thing that I find so interesting

Duncan Barrigan: 00:20:19

about, it's how the two fit together.

Duncan Barrigan: 00:20:21

That if either one of these things go wrong, whether it's your responses or

Duncan Barrigan: 00:20:24

whether it's the record keeping you had in the first place, they're only as good

Duncan Barrigan: 00:20:28

as, the worst of the two of them, right?

Tedd Huff: 00:20:30

I wanna come back to, to the KPI side you mentioned

Tedd Huff: 00:20:33

that they were able to.

Tedd Huff: 00:20:34

To get, 25% of their AR came in within a couple of days.

Tedd Huff: 00:20:39

I'm wondering, how much of this communication flow that you've put

Tedd Huff: 00:20:46

together does it help your clients with more accurate payment, timing

Tedd Huff: 00:20:52

predictions than a traditional ML model?

Duncan Barrigan: 00:20:55

in my days at GoCardless, we built, various models

Duncan Barrigan: 00:20:57

about, payment, timing, predictions You're sort of looking with a lot

Duncan Barrigan: 00:21:00

of payments, but not much depth.

Duncan Barrigan: 00:21:02

And you start, investigating whether the lunar cycle matters and like,

Duncan Barrigan: 00:21:06

because some people are paid on a lunar cycle, so you, you know, you

Duncan Barrigan: 00:21:08

start exploring these variables, whereas our belief is that actually.

Duncan Barrigan: 00:21:12

The depth of information is what allows you to predict this, Because

Duncan Barrigan: 00:21:16

if you know that, uh, that customer has traditionally, uh, over the last,

Duncan Barrigan: 00:21:22

12 months paid on average, 13 days late, and you also, have a signal

Duncan Barrigan: 00:21:28

over here or whatever, that there's a contract, Renegotiation going on, or

Duncan Barrigan: 00:21:32

that their credit rating has fallen or something, that's much richer information

Duncan Barrigan: 00:21:35

than trying to have an ML model.

Duncan Barrigan: 00:21:37

Is just predicted based on other

Duncan Barrigan: 00:21:38

people's behavior.

Duncan Barrigan: 00:21:40

If you've got their email saying, I will pay you next Friday, you can

Duncan Barrigan: 00:21:43

make quite a good prediction about when the payment's gonna be made.

Duncan Barrigan: 00:21:46

'cause you've got their email that says you're gonna be paid next Friday.

Duncan Barrigan: 00:21:48

the real revolution that we are looking to make in a, in the

Duncan Barrigan: 00:21:51

cashflow forecasting side is.

Duncan Barrigan: 00:21:53

one, actually base these predictions on the relationship rather than basing

Duncan Barrigan: 00:21:58

them on data about other people.

Duncan Barrigan: 00:22:00

and number two, kind of a revolution towards bottom up rather than top down

Duncan Barrigan: 00:22:04

forecasting that allows you to manage, to arrange rather than just having to,

Duncan Barrigan: 00:22:09

to suffer from it, We want to get to the point where we can start taking action,

Duncan Barrigan: 00:22:12

we can immediately, 'cause it's an AI rather than a human workforce, we can

Duncan Barrigan: 00:22:16

sweat some of those people a bit harder in order to make sure that you get paid.

Duncan Barrigan: 00:22:19

to reduce the fact that cashflow is the number one cause of businesses failing.

Duncan Barrigan: 00:22:23

even businesses where customers want 'em to survive.

Duncan Barrigan: 00:22:25

we'd love to get to that point where we can actually be doing

Duncan Barrigan: 00:22:28

something about that problem.

Tedd Huff: 00:22:29

it's crazy how all that fits together and, and trying to figure out.

Tedd Huff: 00:22:33

How do you get the data also back into your ERP or your accounting software?

Tedd Huff: 00:22:41

this is one of the places where most FinTech solutions die a horrible death.

Tedd Huff: 00:22:48

I've got one business running that uses completely custom AWS infrastructure.

Tedd Huff: 00:22:54

We built internal ledgering technology from scratch.

Tedd Huff: 00:22:58

There's another group that uses bill.com as their ar ap.

Tedd Huff: 00:23:03

Then we've got some folks who are using Legacy QuickBooks desktop installations

Tedd Huff: 00:23:09

that they're, they're not even using the web version and then when you

Tedd Huff: 00:23:14

look at all these different tools.

Tedd Huff: 00:23:16

Almost everything is tied together with custom APIs or,

Tedd Huff: 00:23:20

robotic process automation.

Tedd Huff: 00:23:23

Most of it's super niche, so the off the shelf solutions don't work without

Tedd Huff: 00:23:28

massive levels of customization.

Tedd Huff: 00:23:31

when I have AR platforms tell me they can replace my entire financial

Tedd Huff: 00:23:35

infrastructure, I question it because what it tends to happen is it forces

Tedd Huff: 00:23:40

My teams and my customers into yet another portal where they have to create another

Tedd Huff: 00:23:45

account, remember some more passwords.

Tedd Huff: 00:23:48

And honestly, that just, becomes a deal killer straight out of it.

Tedd Huff: 00:23:53

you've approached this completely different.

Tedd Huff: 00:23:55

you're positioning Lunos as that invisible orchestration layer that works

Tedd Huff: 00:24:00

with all the chaos we already have.

Tedd Huff: 00:24:02

can you.

Tedd Huff: 00:24:03

Explain how you integrate with this messy reality of solutions that

Tedd Huff: 00:24:11

are out in the marketplace and how it's not just another integration

Tedd Huff: 00:24:17

headache that breaks every six months.

Duncan Barrigan: 00:24:20

we think about ourselves a little bit differently to

Duncan Barrigan: 00:24:22

most platforms, The timeless problem of, businesses paying each other, involves

Duncan Barrigan: 00:24:27

everyone adopting a common standard.

Duncan Barrigan: 00:24:29

That's, just never gonna be the case we think of it in, two ways.

Duncan Barrigan: 00:24:32

One of which is we can get all the data that we need, which really

Duncan Barrigan: 00:24:37

is the same as a human right.

Duncan Barrigan: 00:24:38

if you're trying to imagine how Lunos works, think about how the human would

Duncan Barrigan: 00:24:41

do and then imagine how you could make that work and make it superhuman.

Duncan Barrigan: 00:24:45

So if the human needs to read the CRM, to figure out whether that deal's being

Duncan Barrigan: 00:24:49

renegotiated get the contract in order to check whether the query's right.

Duncan Barrigan: 00:24:54

That means that we need to be able to read the CRM too, right?

Duncan Barrigan: 00:24:56

we think of it as how can we interconnect to get the data email is ultimately, the.

Duncan Barrigan: 00:25:02

web that can fit all of these things together Lunos can actually, as a

Duncan Barrigan: 00:25:05

worker, can do what a human would do and say, well, sorry, hey, CSM, you know,

Duncan Barrigan: 00:25:09

actually, what is going on with this?

Duncan Barrigan: 00:25:11

I think the ability to act as a human is the first defense against all this,

Duncan Barrigan: 00:25:15

People have coped with all of these systems for all this time, and if

Duncan Barrigan: 00:25:20

they can't get the information they need, they find a way around it, The

Duncan Barrigan: 00:25:22

second is that we are not trying to, think everyone is going to adopt Lunos

Duncan Barrigan: 00:25:27

directly and switch over so they, have their login details to the Lunos portal.

Duncan Barrigan: 00:25:32

my belief is it's gonna become agent to agent and we wanna be the agents.

Duncan Barrigan: 00:25:37

We wanna be the people providing the agents to everyone else, it is

Duncan Barrigan: 00:25:40

kind of the world's biggest niche, I suppose I sometimes think about as

Duncan Barrigan: 00:25:42

we wanna be the, the provider of the agent for the world's biggest niche.

Tedd Huff: 00:25:46

a lot of times, these integrations have to happen in order

Tedd Huff: 00:25:50

to, to streamline the workflow, to be able to see the data that you were

Tedd Huff: 00:25:54

talking about, how have you at Lunos.

Tedd Huff: 00:25:58

Moved forward with figuring out what systems to integrate with so

Tedd Huff: 00:26:02

that people don't have to rebuild or reinstall an an entire stack.

Duncan Barrigan: 00:26:09

it is ultimately incredibly strategic for us to be able

Duncan Barrigan: 00:26:12

to integrate with as many things as possible while still getting the data

Duncan Barrigan: 00:26:17

into Lunos for it to be effective.

Duncan Barrigan: 00:26:18

So we've invested a lot in, the.

Duncan Barrigan: 00:26:21

Tooling required to do that.

Tedd Huff: 00:26:22

what kinds of systems has Lunos already integrated to alert

Tedd Huff: 00:26:26

me that I have two different things.

Tedd Huff: 00:26:28

One of my CRM and one of my ERP.

Duncan Barrigan: 00:26:30

the base data for us is the ERP.

Duncan Barrigan: 00:26:32

NetSuite, QuickBooks, Xero, Stripe invoicing And we're

Duncan Barrigan: 00:26:37

rolling out many more as we go.

Duncan Barrigan: 00:26:39

we are, Pushing HubSpot and Salesforce as the obviously dominant

Duncan Barrigan: 00:26:44

CRMs of choice and email and Slack are the really big comms ones.

Duncan Barrigan: 00:26:48

Slack is actually the one I'm personally most excited about because, as an

Duncan Barrigan: 00:26:52

entrepreneur and founder myself, like.

Duncan Barrigan: 00:26:54

I just don't wanna be logging into all these systems.

Duncan Barrigan: 00:26:56

when we use Lunos on ourselves, which for our customers, they will

Duncan Barrigan: 00:26:59

obviously also have their invoices and their billing handled by Lunos.

Duncan Barrigan: 00:27:03

I will just be asking Slack.

Duncan Barrigan: 00:27:04

Hey, what's going on with, FinTech Confidential?

Duncan Barrigan: 00:27:06

have they paid us yet?

Duncan Barrigan: 00:27:08

Uh, and I will be expecting

Tedd Huff: 00:27:09

And the answer is no.

Tedd Huff: 00:27:11

No, we have not.

Tedd Huff: 00:27:12

Duncan.

Duncan Barrigan: 00:27:12

Tedd has not paid that invoice yet.

Tedd Huff: 00:27:16

those integrations are fantastic, what is Lunos's strategy

Tedd Huff: 00:27:19

around APIs and allowing agents and other bespoke systems to connect

Tedd Huff: 00:27:25

into the system that you've built.

Duncan Barrigan: 00:27:28

I think the future is agent to agent, but there is still

Duncan Barrigan: 00:27:31

gonna be a bit of work to get there, one aspect of this, that I've experienced

Duncan Barrigan: 00:27:36

the hard way at GoCardless is if you are.

Duncan Barrigan: 00:27:38

Never been the person that directly owns the customer relationship.

Duncan Barrigan: 00:27:42

You can't actually build the best version of it yourself in the first place.

Duncan Barrigan: 00:27:45

we are starting with working directly with merchants 'cause frankly, most of our

Duncan Barrigan: 00:27:49

best ideas come from working with them.

Duncan Barrigan: 00:27:51

I think through that journey it's about.

Duncan Barrigan: 00:27:53

Getting the relationship with the humans, right, for an agent, agent number one

Duncan Barrigan: 00:27:58

first before we start adding in the rest of the agents and getting all of the

Duncan Barrigan: 00:28:03

interactions with the other systems, we need to make sure everything's working

Duncan Barrigan: 00:28:07

reliably on both sides before connecting those two together and entering a

Duncan Barrigan: 00:28:11

fully automated agent to agent flow.

Duncan Barrigan: 00:28:14

our strategy is to start on the AR side.

Duncan Barrigan: 00:28:16

With the AR agent and make that work as well as possible with

Duncan Barrigan: 00:28:19

the humans and the systems.

Duncan Barrigan: 00:28:21

then from there, start working across AR and AP to make the

Duncan Barrigan: 00:28:24

agent to agent, vision a reality.

Tedd Huff: 00:28:27

Duncan, you've recently launched publicly into market

Tedd Huff: 00:28:30

that has fundamentally been manual since commerce began thousands

Tedd Huff: 00:28:34

of years ago using clay tablets.

Tedd Huff: 00:28:37

as someone who's built FinTech companies for over 25 years, I've witnessed multiple

Tedd Huff: 00:28:42

technology revolutions, shape, entire industries, and I can tell you that.

Tedd Huff: 00:28:48

What we're talking about right now sounds a lot like science fiction,

Tedd Huff: 00:28:53

but it's possible that we end up in a fully autonomous AI negotiation

Tedd Huff: 00:28:59

in the next three to five years.

Tedd Huff: 00:29:02

So what I want you to do, this is my favorite part of the episode.

Tedd Huff: 00:29:06

What I want you to do is I want you to, to look deep into my crystal ball.

Tedd Huff: 00:29:11

Look.

Tedd Huff: 00:29:11

Look deep, deep into it.

Tedd Huff: 00:29:12

And I want you to go look and look into like 2028 to 2030.

Tedd Huff: 00:29:20

how do you see AI's negotiating and reshaping this $70 trillion B2B landscape?

Tedd Huff: 00:29:29

And what does it look like to you?

Duncan Barrigan: 00:29:32

think that I I once it starts, it's actually

Duncan Barrigan: 00:29:34

going to be surprisingly quick in some parts of the economy.

Duncan Barrigan: 00:29:38

stage one is single agent to single agent, and stage two is the network

Duncan Barrigan: 00:29:43

of agents and the real magic for the economy and for us, as individuals

Duncan Barrigan: 00:29:47

rather than founders of companies in the space is, is the network side.

Duncan Barrigan: 00:29:51

let's start with the, the, the agent to agent.

Duncan Barrigan: 00:29:54

two companies do business.

Duncan Barrigan: 00:29:57

there have been people and agents involved in all sides discussing that.

Duncan Barrigan: 00:30:01

it comes to settling it, is a question of communicating agreeing on data and a

Duncan Barrigan: 00:30:07

question of what is ultimately actually a negotiation about the terms and

Duncan Barrigan: 00:30:11

how those terms merge into a reality.

Duncan Barrigan: 00:30:14

I imagine a world where.

Duncan Barrigan: 00:30:16

within possibly seconds, if the humans have set up all the data or possibly

Duncan Barrigan: 00:30:21

days, if the agents are still chasing the humans about this, the two sides will come

Duncan Barrigan: 00:30:27

together and have agreed, you know what?

Duncan Barrigan: 00:30:30

Okay, this data is all correct.

Duncan Barrigan: 00:30:32

We have resolved whether the, as, as per your story we have resolved, whether

Duncan Barrigan: 00:30:37

is the correct record of all of this,

Duncan Barrigan: 00:30:39

this would've been solved in an instant by both sides comparing their record

Duncan Barrigan: 00:30:43

and then ultimately sitting there.

Duncan Barrigan: 00:30:44

And this is where the real negotiation part comes.

Duncan Barrigan: 00:30:47

Real power comes from the fact that this is a network.

Duncan Barrigan: 00:30:50

Company A Os, company B, and company B os company C. we have started

Duncan Barrigan: 00:30:56

creating chains and networks of how these things fit together.

Duncan Barrigan: 00:31:00

ultimately the, the part I'm most excited about, I've had friends

Duncan Barrigan: 00:31:04

whose businesses failed because of.

Duncan Barrigan: 00:31:06

Because of cash flow and their customers didn't want 'em to fail, and their

Duncan Barrigan: 00:31:09

customers wanted them to continue and they loved their product, but it didn't work.

Duncan Barrigan: 00:31:13

once you have a network of agents, you can negotiate and say,

Duncan Barrigan: 00:31:16

There's a company over here elsewhere in the supply chain that is perfectly willing

Duncan Barrigan: 00:31:20

to pay now in exchange for a 2% discount.

Duncan Barrigan: 00:31:23

And there's a company, four steps down the chain that is actually really struggling.

Duncan Barrigan: 00:31:25

the whole thing can just.

Duncan Barrigan: 00:31:27

Hyper efficiently manage that negotiation a way that is completely impossible.

Duncan Barrigan: 00:31:32

if it's all humans and everyone's responding to their emails,

Duncan Barrigan: 00:31:35

there's no way that's gonna happen.

Duncan Barrigan: 00:31:36

But if it's gonna ripple through the chain, then suddenly we end up with

Duncan Barrigan: 00:31:40

something that will really benefit all of us because, you know, great products,

Duncan Barrigan: 00:31:43

great businesses, great people, will.

Duncan Barrigan: 00:31:46

in a better position to thrive because this gunk that is in the way and

Duncan Barrigan: 00:31:50

all of these emails and these slow interactions won't be there anymore.

Duncan Barrigan: 00:31:53

So it's the network of agents that gets me really excited,

Tedd Huff: 00:31:57

being a FinTech founder, and we have a large audience of FinTech founders

Tedd Huff: 00:32:03

and executives, if you were to give them.

Tedd Huff: 00:32:06

One piece of advice, and it's the only advice that they could ever

Tedd Huff: 00:32:10

use going forward, what would it be?

Duncan Barrigan: 00:32:13

Focus on solving the customer's problem as best as you can and

Duncan Barrigan: 00:32:18

let everything else take care of itself.

Tedd Huff: 00:32:20

what does that mean?

Duncan Barrigan: 00:32:21

it's really easy as an executive, as a founder to get caught

Duncan Barrigan: 00:32:28

up in the business and the metrics and like these things are important.

Duncan Barrigan: 00:32:32

Look, I'm a, I'm a data-driven person.

Duncan Barrigan: 00:32:34

I think these things are important.

Duncan Barrigan: 00:32:36

I think the experience of my, you know, when you are holding a hammer,

Duncan Barrigan: 00:32:39

everything looks like a nail.

Duncan Barrigan: 00:32:40

that was part of leading me to found Lunos was a reminder for me that.

Duncan Barrigan: 00:32:44

It's very easy to get caught up in that to the detriment of seeing the bigger

Duncan Barrigan: 00:32:47

and smaller picture at the same time.

Duncan Barrigan: 00:32:49

So, as a product guy, as a chief product officer, I thought I was

Duncan Barrigan: 00:32:53

living by this, focus on customer problems, solutions come second.

Duncan Barrigan: 00:32:57

I think it's not just a reminder for executives and founders everywhere that.

Duncan Barrigan: 00:33:01

It's really easy to lose sight of that.

Duncan Barrigan: 00:33:03

And it's one of the things that, that sort of obsessive customer problem

Duncan Barrigan: 00:33:06

focus is something I want to do my best to, to live up to at Lunos.

Duncan Barrigan: 00:33:10

if you live up to that, it's quite hard for things to go too far off.

Tedd Huff: 00:33:13

great advice.

Tedd Huff: 00:33:14

something that we all need to be reminded about, this has been like a conversation

Tedd Huff: 00:33:19

I. More of a masterclass really in strategic thinking and technology vision.

Tedd Huff: 00:33:25

we've covered your journey from cardless to attacking this $70

Tedd Huff: 00:33:31

trillion B2B payments market.

Tedd Huff: 00:33:33

Not only that, but we've also talked about how Lunos is revolutionizing

Tedd Huff: 00:33:38

the way we look at accounts receivable by training it as a communication

Tedd Huff: 00:33:42

and negotiation challenge.

Tedd Huff: 00:33:45

Rather than just this workflow problem.

Tedd Huff: 00:33:47

looking at it from the perspective of what would a human do, you're

Tedd Huff: 00:33:50

building this seamless integration without forcing people into

Tedd Huff: 00:33:55

major infrastructure changes or.

Tedd Huff: 00:33:58

Yet logging into another portal, which is always my favorite thing to do.

Tedd Huff: 00:34:02

If you haven't already, go ahead and head over to lunos.ai and check it out.

Tedd Huff: 00:34:08

It could help you get paid quicker.

Tedd Huff: 00:34:10

So thanks again for joining us Duncan.

Duncan Barrigan: 00:34:12

Thank you so much for having me.

Duncan Barrigan: 00:34:13

It was really fun

Tedd Huff: 00:34:14

That does it for this episode of FinTech Confidentials

Tedd Huff: 00:34:17

Leaders one-on-one series.

Tedd Huff: 00:34:20

And if these conversations, they're really designed to give you more

Tedd Huff: 00:34:24

than just a service level soundbite.

Tedd Huff: 00:34:26

They're here to show you how real operators think, lead, and

Tedd Huff: 00:34:30

make things happen in FinTech.

Tedd Huff: 00:34:32

if you got value from today's episode, make sure you're subscribed

Tedd Huff: 00:34:35

so you don't miss another one.

Tedd Huff: 00:34:36

You can find us at YouTube, Spotify, apple podcast, or wherever you listen.

Tedd Huff: 00:34:40

if you want to go deeper into what we're tracking behind the scenes,

Tedd Huff: 00:34:43

sign up at fintechconfidential.com and share this with someone who's

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serious about where FinTech is going.

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And as always, keep moving forward.

Tedd Huff: 00:34:53

As we wrap up today's episode, I've got one last thing for you.

Tedd Huff: 00:34:57

If you are in the trenches fighting fraud and financial crime, you

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know it's a complex battlefield.

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That's where hawks AI tools for real time payment screening

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a ML transaction monitoring.

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And dynamic customer risk rating come into play.

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These aren't just buzzwords.

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They're game changers.

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Designed to make your compliance more effective and less of a headache.

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Imagine slashing through false positives with precision and giving your

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compliance strategy the edge it needs.

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Head on over to get Hawk ai.com to sign up for a demo and discover how their

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platform can revolutionize how you

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fight fraud and financial crime.

Lily Eleven: 00:35:39

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Lily Eleven: 00:35:43

This is provided for informational purposes only.

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It is not offered or intended to be used as legal, tax, investment,

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financial, or other advice.

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We strive to provide accurate and UpToDate information, but will

Lily Eleven: 00:35:54

not be responsible for any missing facts or inaccurate information.

Lily Eleven: 00:35:58

You comply and understand that you should use any of this

Lily Eleven: 00:36:01

information at your own risk.

Lily Eleven: 00:36:02

Cryptocurrencies are highly volatile financial assets, so research and

Lily Eleven: 00:36:06

make your own financial decisions.