Marc Held: 0:03

That's simply because data enables us to understand the risks inside of the global supply chain. For us, as long as we can put a box around the individual transaction and truly understand whether or not something's gonna go wrong. Truly understand whether or not stuff's gonna get repaid. We believe that to be a fairly comfortable risk. And, and so it's just been, again, throwing butt loads of data at the problem to see if we can kind of extract as much risk as possible while providing as much value as we can to our customers

Tom Raftery: 0:34

Good morning, good afternoon, or good evening, wherever you are in the world. This is the Digital Supply Chain podcast, the number one podcast focusing on the digitization of supply chain, and I'm your host, Tom Raftery. Hi everyone. Welcome to the Digital Supply Chain podcast. My name is Tom Raftery and with me on the show today, I have my special guest. Marc. Marc. Welcome to the podcast. Would you like to introduce yourself?

Marc Held: 0:58

Howdy. Thanks for having me on. I'm Marc I run a company called Fishtail where we help the next generation of freight forwarders compete with the big guys.

Tom Raftery: 1:10

Okay. And how?

Marc Held: 1:13

So I don't know if you guys are, are super familiar with the, with the world of freight but generally, speaking like if I'm Proctor and Gamble and I need to move something from point A to point B there's probably a couple of hops that that need to get done. You've got someone who's gotta put something onto a shipping container, someone's gotta move the shipping container. A completely different company moves the shipping container out of the port into the final distribution center. Usually that stuff is, is coordinated by something called a freight forwarder. And, and one of the big next generation freight forwarders that people are starting to see is a company called Flexport. There's a lot of 'em out there. Dhl, al ups even does some freight forwarding. And so, as more and more of these companies have started to go out into the world we start to see them providing more and more services. And so Flexport now ports, we port like, there's a bajillion of these folks that are, that are poking around now. They're able to provide financial services that a lot of other freight forwarders aren't able to simply because, you know, banks generally don't lend to forwarders. They don't generally lend to, the geographies that, folks are, are touching. Plus sometimes the, the, the actual cost of, moving stuff doesn't make sense for the banks to underwrite. And so what, what Fishtail does is we effectively work with the other freight forwarders to enable them to get financing. And that kind of manifests itself in kind of one of two ways. Or we'll either provide financing directly to the forwarder so that they can extend that terms. So, use case of this is Proctor and Gamble, wants DHL to move something from point A to point B. P and g probably doesn't wanna pay immediately upon delivery. They, they wanna pay after 30 days, 60 days, 90 days. But DHL's gotta pay all of the service providers along the way. And so we basically bridge that gap so that DHL doesn't have to pony up the cash to actually take on that, that order. And, and our specialty is arming the 99% arming the rebels who don't necessarily have the balance sheet to do this. Secondarily, we also enable the, the logistics companies to provide trade finance to their customers. And when I say trade finance, I'm mostly talking about financing the procurement of the goods. So again, for this p and g use case, let's say Walmart sends an order to p and g. P and G's gotta spend money to get the stuff made. So let's say I gotta make 10,000 cases of shampoo, P and G's gotta go buy the chemicals. They've gotta go manufacture the product and then they gotta move it. So we're, we're basically enabling the freight forwarders to enable lending to Proctor and Gamble for the full soup to nuts cycle. So DHL can now not only fund the order from Walmart, but they can fund the movement of, of those goods so they can take on, more and more more and more customers. Does that, does that make sense?

Tom Raftery: 4:01

It does. I, I, I understood 99% of it and I don't have a, I don't have a finance head, so, you know, kudos Well done for that. How?

Marc Held: 4:10

How do we do this? So it turns out that all of this stuff is insanely complicated. So, so in like, just to give you a little bit of context, and I don't want to get into super nitty gritty details. Let's say you're in the United States and you're buying a house. The bank gives you a mortgage and then they file all sorts of, you know, legal things against your house. It turns out that it's very similar in international trade. So if someone's gonna be funding a shipment, if someone's gonna be funding something, you gotta go into every country, every jurisdiction, that stuff is moving through and you gotta make sure that you're compliant in all of those, those areas. And so we built tech that basically automates that compliance aspect. We built tech that automates the credit risk side. So we're constantly predicting what's the likelihood that Walmart is gonna pay p and g? What's the likelihood that, this port isn't gonna have a major disruption, which is gonna change, when the product is gonna get delivered. What's the likelihood that you're not gonna get stuck in customs? Can this manufacturer even deliver on this, order which requires a, a boatload of data. Like we are literally tracking every boat in the water, every plane in the sky. We're looking at trucks, we're looking at, International transactions we're even doing weird things with currencies. Like the scope of the data that we're, we're actually looking at to, to make this stuff happen is incredibly immense. And I also should, should mention for, for context personally, I've started and sold a couple of companies in the supply chain intelligence space. And so a lot of what we're doing now is basically, layers on top of some of the work that I've been doing over the past 10 15 years. Does that, does that

Tom Raftery: 5:45

Yeah, yeah. You're, you're examining pardon the pun boatloads of data and you, you're then creating, let's call it credit risk scores for people, well, people no, but organizations and then deciding based on the credit risk scores, whether to give them money for a particular trade. And if so, what kind of cost of capital to apply to that to that.

Marc Held: 6:13

Exactly, you hit the nail right on the head. And, and one thing that I kind of wanted, you know, poke into is one of the things that makes this specific model unique is generally speaking, when you're talking about trade finance or, or sort of any finance in general. Banks will fund invoices. So banks love touching stuff after it's already done. And they want to just take the risk that, you know, Walmart's gonna repay p and g because they, you know, they can understand it, they can predict how credit worthy Walmart is. They can, there's no risk in terms of not being able to deliver any of the stuff. We think that's complete nonsense. 99% of the time you need cash before you even start making a thing. So as I was mentioning earlier about this Proctor and Gamble use case where they have to spend money to, actually procure the raw materials, get the stuff manufactured, start moving it. Majority of the actual need for capital is before the stuff is actually delivered. And that's kind of what our technology enables. I mean, we fund purchase orders, we fund small businesses, we touch emerging markets. We basically fund the stuff that HSBC doesn't want to touch. And that's been kind of one of the main driving forces is to, you know, why we enter the markets that we do. We do a lot in LATAM, we do a lot in Africa, we do a lot, you know, all over the place. And that's simply because data enables us to understand the risks inside of the global supply chain. For us, as long as we can put a box around the individual transaction and truly understand whether or not something's gonna go wrong. Truly understand whether or not stuff's gonna get repaid. We believe that to be a fairly comfortable risk. And, and so it's just been, again, throwing butt loads of data at the problem to see if we can kind of extract as much risk as possible while providing as much value as we can to our customers.

Tom Raftery: 8:00

Okay, cool. And on the value to your customers, one. There's typically a whole scale of how much the cost of capital is. Everything from kind of loan sharks on one end, maybe banks in the middle, and friends and family at the other side. I'm sure you're not in the friends and family side of it, but I'm also presuming you're not on the loan shark side of it and there's kind of banks in the middle. Where do you, where do you kind of fall on that scale?

Marc Held: 8:25

So, so that's a great question. One of the other strange things about Fishtail is that we're actually like a market maker where we work with multiple pools of capital to match together the right pool of risk to the right pool of capital. So let's say I'm Proctor and Gamble, odds are p and g is probably gonna get really cheap money from whatever capital providers. If I'm, you know, a small business. In a market that there's not a lot of money, I mean, it's probably gonna cost a little bit more. And that's simply a fact of, you know, demand. Can we match together, supply and demand to like truly get the stuff moving. But one of the things that we've been working on recently is something that we've been calling sustainable trade finance. So it's sustainability for us. Means a lot of things e, s and G. There's, you know, this big bucket of, you know, do you care about things that impact the environment, things that are socially good and things that have good corporate governance. And part of our hypothesis is that we can enact real change in the global supply chain by working with pools of capital that want to do good and put it to work in areas where it actually can. And so, A lot of this impact money, this ESG money, we can start pushing into markets that are traditionally underfunded. Traditionally, In the lone shark territory so that we can drive down costs so that these businesses can actually operate. We also have a, a broad environmental product that, that we'll be launching in the, you know, coming weeks where we predict the CO2 missions for everything that moves, and we can use that to change the interest rate of our financing. And this is purely an opt-in model where, if you want access to this pool of capital, we've just gotta monitor your, your shipments cuz fun fact, if you've got one ship that's going from point A to point B, ship that, that was made in the 1980's s versus one that was made a few years ago. Turns out the ship that was made in the eighties is actually way more efficient from a, a CO2 emissions perspective than than some of the more recent ones. And that's a function of a lot of things. It's, you know, engine, it's fuel consumption, utilization, it's a lot of stuff. And so one of the things that we're doing is just trying to predict what's going to happen. Predict all the ways to get from point A to point B. Assume that, you know, the vessels aren't going to be just sitting out in the middle of the ocean for, God knows how, how long burning bunker fuel. And then see how we can compare all of the different options to incentivize good behavior. Does that, does that make sense? I

Tom Raftery: 10:45

Yeah. Except,

Marc Held: 10:46

little bit of a tangent.

Tom Raftery: 10:47

yeah, but No, but I just, I'm curious cos you said something that was hugely counterintuitive to me. You said that a ship made in the eighties is far more fuel efficient than one made recently. I would've assumed it would be the reverse. How does.

Marc Held: 11:02

it's been all about cost optimization. So, so these big like triple E vessels, the ones with like 20,000 containers on or TEU on ' they're optimized for, slow steaming. They're gonna try to go as slow as they can to conserve fuel. And because of the characteristics of these engines, they're generally operated under this, optimal fuel band, which means that they're just burning fuel. And a lot of the fuel that ends up getting used is, you know, bunker fuel in the middle of the ocean. And then as you get closer, there's a, you know, the sulfur reduced stuff. But it's just, again, a pure function of how these fuels, that these engines are being operated in a non-intuitive manner just to conserve costs.

Tom Raftery: 11:45

Okay. Bizarre. Okay. I guess it makes kind

Marc Held: 11:48

it's very strange.

Tom Raftery: 11:50

I guess it makes kind of financial sense if not carbon sense.

Marc Held: 11:53

mm-hmm.. Mm-hmm.

Tom Raftery: 11:55

And we need to sh we need off topic, but that's something we need to address in terms of making carbon intensive operations more expensive.

Marc Held: 12:05

Well, and so this is one of our, kind of mantras around why we're doing the things in, in the sustainability world that we are. I come from the maritime world. We love the maritime people. They're never gonna change unless there's economic incentives to do so. Like you could not pay MSC enough money to change their ships, you could not pay. literally if we were gonna give them a billion dollars, they're never gonna do anything about it. The only thing they're gonna do is listen to customer demand. And so one of the things that we're trying to do is incentivize folks to work with the better ships, work with the better route, work with the better carriers on a per transaction basis. Cause as I was saying earlier, it's literally, you know, orders of magnitude two ships that are going the same route. And again, that, that could be a function of how well utilized that ship is. It could be a function of the engine age and the shape of the ship. And, whether or not it's a direct sailing or the trans shipment where it's gotta make a hop. Cause it turns out that, a lot of the, folks that are doing trans shipment actually have relatively efficient vessels. But the impact there is that it might be a little bit longer in terms of a duration. So like we're, we're not, people still have to get stuff from point A to point B, so we can't, screw people over by charging them a boatload of money for making these decisions. They still have to operate their business. It's just being able to figure out in context what makes sense to actually get things done in a reasonable way.

Tom Raftery: 13:25

Okay. And this sustainability angle that you have, is that just out of pure personal desire for the world to be a better place? Or is it that your customers are screaming for it, or where is it coming from?

Marc Held: 13:40

Yeah. I'm, I'm, I'm a dirty hippie vegan. I'm, I'm, you know, trying to lean into doing as much as I can from the sustainability aspect. I mean, personally, there's only so much you can do. I'm a big fan of, these judo mind tricks where you can leverage people's greed to actually do good. And, one of the neat things about the trade market in particular is there's a lot of money that wants to get put to work. Like trade finance as an asset class looks a lot like real estate. From a risk adjusted return perspective. So you get a lot of people that traditionally invest in real estate who wanna start investing into, into trade finance. We're just enabling them to do that in a sustainable way, which unlocks pools of capital that are traditionally not put to work in the space. So, like, personally, I have a, you know, a vendetta against CO2 emitters, but from an economics perspective, Like, we're effectively just trying to put money to work that hasn't been able to get put to work into places that absolutely need money. So pure, pure, pure capitalism. Capitalism for good

Tom Raftery: 14:43

there we go. There we go. And you talk about global supply chains, are you therefore operating globally or is it US or is

Marc Held: 14:55

yes. We, we are lending all over the place. So we, we do a lot of work in Latin, Africa, Europe, the Americas you know, pick a region. Odds are we do something in that space. Which is, I would argue something that's relatively novel. Cuz again, it's all about data. Like traditionally speaking, you've folks like HSBC who are really only gonna lend in places where they have a physical presence. And that's again, just because they have to go to the governments and, you know, register security interests in the things that they're, they're doing. And when stuff goes wrong, they gotta, you know, go beat up the, the, the, the borrowers, you know, where we don't, we don't have these problems. So we're kind of not necessarily limited by any of these traditional methods, which is also another one of the reasons why we are able to work with freight forwarders. Freight forwarders, generally speaking from from our experience, have been able to touch multiple jurisdictions. I mean, yes, a lot of forwarders like specific regions, they like specific trade lanes. But that just makes it more interesting to us because we can spread risk across multiple forwarders. We can spread risk across multiple regions which makes us kind of one of these weird little antifragile businesses.

Tom Raftery: 16:06

Fascinating and that boatloads of data that you're going through,

Marc Held: 16:11

Mm-hmm.

Tom Raftery: 16:12

you must need some pretty fancy AI to be able to go through it.

Marc Held: 16:17

Mm-hmm.. I, I would argue that we're doing a lot of stuff that's kind of at the bleeding edge of all the AI ml pots we're doing a lot of stuff in document understanding, so we're predicting, the content that's inside of a bill of lading without having to do the traditional, like, here's a box, let's do some ocr, optical character recognition to figure out what this text means. So we're just throwing deep neural networks at the problem and these transformer models to see what we can extract from the data. We're doing all sorts of crazy things in long short term memory to predict where vessels will be and you know, where they're going next and all this other stuff. So, a lot of bleeding edge stuff. One of the things that's, that's relatively weird about the global supply chain is that, you know, whenever you analyze this stuff, it tends to be geospatial, temporal. Usually people are touching maybe two of those things. And so geospatial, temporal for, for those who aren't super familiar is basically things that are in space time. Usually you have things that are analyzing things in space, or things in time, but when you start merging those two worlds together, it like creates a whole entire different complexity of like, how do you analyze that stuff? You know, what kind of tech do you use to actually store the data? The data underpinnings are relatively challenging to get right.

Tom Raftery: 17:39

Okay. And how do you get it right? I mean, how do you, how do you judge? How do you make sure that it doesn't mess up and say, no risk here, and you put a boatload of money into it and suddenly

Marc Held: 17:54

Yeah. I mean there, there's a lot of trial and error. I mean, a lot of the, the training that we do on our models to do some of this, like credit risk stuff, you know, We always back test. We always make sure that, there is some sort of, you know, it's, it's hard to build explainable AI models. It's just like AI has become this big black box where like you throw data in, some magic happens and then stuff gets spit out. So it's kind of hard to like truly understand why the AI is making the decisions it's making, we're trying our best to, to like explore some of these explainable AI methods. And simply because we, like, we work in a relatively regulated industry, you know, banks generally have to deal with basal compliance and, that means that they can't use a lot of these methods. So, I guess, I guess what I'm trying to say is it's hard. It's very hard. It takes a lot of time and kind of some expertise in making sure that you're not just making dumb mistakes everywhere. So a lot of testing.

Tom Raftery: 18:52

Sure, sure. Any customer success stories you can talk to?

Marc Held: 18:56

Yeah, yeah, yeah, yeah. I mean, we we love, we love our customers. So I, I'll, I'll use one, one customer that we're particularly excited with just because they, they let us test all sorts of fun things with them. They're freight forwarder in the US that works in a lot of markets. We basically started working with them and they were probably doing, you know, under a million dollars a year in revenues. Relatively small business. But they kept on losing business to Flexport. They kept on losing business to a lot of these digital freight forwarders. And that's simply because these forwarders were able to provide these financing terms. They were able to provide longer terms. They're able to provide, inventory, financing, purchase order financing. And so when we started working with this customer, you know, again, they were relatively small. We embedded ourselves directly into their workflow and basically became their AR and AP automation tool. So we, we are paying their suppliers, we're getting repaid by their customers. We're making it super easy so that we effectively have become the, finance arm of this business and month over month, they've been growing to a point where they're, they've gone from a million a year to over 2 million a month. And that's literally in just being able to take on more business while keeping the same customer service level, which is something that a lot of the forwarders that, that are competing with Flexport are, are, are really specialized in. They provide great service. They understand their markets well. They understand what they're good at. And they let us be their capital partners. So I guess that that million a year to couple million a month case study we're, we're particularly proud of. We also do a lot in I guess in the pharmaceutical space. We have another customer that, that imports insulin into Mexico. When we started working with them, they were probably doing a couple hundred thousand dollars a year. Small, small company over the past year, I mean, we're, we're lending, we're writing checks for, you know, three plus million dollars a transaction. So, like, again, we see this pattern happen over and over and over again, where the minute we start working with a company, we can unlock working capital so that our, our customers can do the things that they're great at. They can take on bigger orders, they can, not have to tie up their, the, the own capital to, to pay their. Their customers or their suppliers. And that enables them to, to grow relatively rapidly,

Tom Raftery: 21:12

Nice. Nice. I know we touched on sustainability already, but is there any other aspects of sustainability that you're helping your customers achieve their sustainability goals?

Marc Held: 21:21

Yeah. Yeah. So, so we, We have one customer that we're working with that is literally redesigning their supply chain specifically to get better interest rates from us. So that's, that's another, neat little tidbit around this, capitalism driven sustainability stuff. But we'll, we'll also look at, how well people are paying their employees. We're doing some work in, you know, safety scores on, vessels to make sure that people aren't being thrown off ships all the time. So, so e es and G like, You're getting me started on the complexity of, of sustainability. Like ESG means a lot of different things to a lot of different people, you know, so we, we have some pools of capital that we work with that like really want to be working specifically in Latin America and like that to them means esg. We have other folks that really care about, water pollution. That to them means esg. So like, ESG means a lot of different things to a lot of different people. We're just trying to be as smart as we can in pulling in data to enable folks make the right decisions for them. On the social side, we've got payments, you know, making sure that people are being equitably treated. We have our borrowers, fill out documentation to, say that they're doing this, not that, that they're, you know, paying their employees fairly, that they're not using slave labor. There's, some low hanging fruits there. But we also do deep tier supply network analysis to basically figure out whether or not folks are doing things in shady ways. And that's helpful on the governance side, just to make sure that no one's funding terrorism by accident or doing any sorts of weird, weird stuff like the, the global supply chain is so weirdly intermingled and intertwined that it blows my mind how some people are able to, operate in it.

Tom Raftery: 23:04

Cool, cool, cool. And where to next for Fishtail? what are your, your plans for global domination, how are you getting there?

Marc Held: 23:11

Yeah, I think, you know, how do you, how do you move a mountain is, you know, one spoonful at a time. Is that the metaphors? I mean, we're just slowly and steadily trying to make sure that we're able to, lend money to people who need it. We wanna make sure that we are being as valuable to our customers as we can be. So, so we're, we're doing a lot in the sustainability side. I think in the coming weeks we'll be doing some announcements, so kind of keep, keep an eye out there. But for us it's just opening up new markets, offering new financing products. Making sure that, you know, we can build the pipes for, for international trade in a way that is truly valuable to our customers. I mean, heck, we, we are even, providing a standalone document understanding product. We have a standalone, supplier payment product that we're, we're probably going to be launching relatively soon. But just making sure that we can build stuff that provides value.

Tom Raftery: 24:07

Okay. Nice, nice. We're coming towards the end of the podcast now Marc, is there any question that I have not asked that you wish I had or any aspect of this we haven't touched on that you think it's important for people to be aware of?

Marc Held: 24:21

Yeah, I mean, I, think I'm kind of in this sustainability head space right now. So I, think. It's not necessarily a question that, that I think you should have asked. I mean, I think you've done a great job, so Mazel tov. But one of the things that I would love to talk about briefly is, is just the fact that sustainability and green washing is very much a real thing. I think over the next couple of years we're gonna start seeing a lot more people do things, quote unquote, in the sustainability world. But it's gonna be a lot of people, you know, saying Tesla is an ESG stock. We see this a lot in the, in the financial world there, you know, regulations are, great in theory for trying to mandate what ESG means or what environmentally conscious means, or you know, what, what all these things are. But. My issue with a lot of these regulations is that, the decisions that are being made aren't necessarily very well informed. Like the supply chain for me seems like it's one of the most underserved parts of the ESG thing because, I don't know how, how deep the, the audience is in kinda scope one and scope two, scope three emissions. You've got people that are interested in measuring your own internal operations. Kinda scope one stuff. Scope two is, the energy impact of, your manufacturing facility or, or your, your office. And then scope three is kind of the secondary knock on stuff. No one is looking at Scope three in any sort of meaningful way, and that's just because it's really hard to get that data. But I think if you can start measuring data at least in a, a, substantial way, you don't have to be perfect, but you can start moving things in, in a, in a direction that actually can drive value. Cuz you know, out of sight, out of mind is, is, is great for a lot of things, but when you're talking about CO2 emissions, this stuff adds up really fast. So, you know, I think greenwashing is something that, that as an industry we have to be really careful about that we're not just, saying that we're doing sustainability things to do sustainability things and, and take advantage of some of the, the, the money that's out there, I mean, Yes, I know that's a little, you know, counter counter to what I was just saying about, you know, tying money to, to the stuff. But like, we're actually measuring our impact and, we have formal verification of, how we're doing all that stuff. But it also goes to, people need to start working together to define what these specifications are. I think one of the things that, like as a supply chain person, no governmental entity is going to any of the people that are actually doing things in supply chain. To like truly understand what it means to have a sustainable supply chain. And so I, I would argue that someone needs to create some sort of consortium or some sort of mechanism to enable true data sharing across organizations, across, you know, the different stakeholders, carriers, forwarders, BCOs, cargo owners retailers. Just to truly define once and for all, what does it mean to have a sustainable supply chain? So that's just my, my soapbox for the, for the day.

Tom Raftery: 27:19

Good. Good, good, good. Okay, Marc, if people want to know more about yourself or Fishtail, or any of the things we discussed on the podcast today, where would you have me direct them?

Marc Held: 27:30

Yeah, you can follow us on LinkedIn. We, we do a lot of our social media work there. We'll send a link you know, in the, in the, in the notes. But just search for Fishtail and we're probably up there somewhere.

Tom Raftery: 27:41

Cool. Cool. Great, great, great. Fantastic, mark. It's been really interesting. Thanks a million for coming in the podcast today.

Marc Held: 27:47

Thanks for having me. It's been a pleasure. Okay, we've come to the end of the show. Thanks everyone for listening. If you'd like to know more about digital supply chains, simply drop me an email to TomRaftery@outlook.com If you like the show, please don't forget to click Follow on it in your podcast application of choice to be sure to get new episodes as soon as they're published Also, please don't forget to rate and review the podcast. It really does help new people to find a show. Thanks, catch you all next time.