Anchor 0:04
So I want to introduce you to your panel and then I’m just going to turn it over to them and let them have it. Your speakers are Matthew, He prefers Debbage with credits. If you if anybody else pronounces it won’t be that way. But that’s how he likes it. Jerry Flom, who is the chief executive officer and chairman of the board of CreditRiskMonitor. Jerry. Thank you. Greg Johnson, who is senior director, and he will be our moderator today. Thank you. And Mike Flom, who is industry practice lead at credit risk monitor. There’s a lot of expertise up here. And they’re going to share it with you now. So take it away, Greg. All right.
Greg Johnson 0:52
So just to clarify, Mike is that credit risk monitor and I’m at Moody’s Analytics, but I’m sorry, this is one time when the guys that are all data geeks can come together, whether we’re competitors or not, and try to demystify this, this credit making process for you all. So we’re just gonna dive right in if that’s okay, and get so we can get to the questions. And first question for Matt. When you look at all of the process around credit decision making that type of thing, it seems like the opportunity for risks to pop up in the process sort of unknowingly and surprising, is there no matter how much we cover your bases, you want to just share any thoughts you might have on pitfalls or places landmines that people might run into in their credit card making process that they’re not thinking about? Typically,
Mathew Debbage 1:35
I mean, obviously, I think most of us know most of the landmines, you know, like if payment data changes, you see a company starting to pay late. So I’ve tried to come up with a couple of areas that not every credit professional always thinks through. So the first one is the group structure. So you’ve got a group of companies all connected, all owned by an ultimate holding company. The first thing is lots of credit professionals, they don’t realise they’ve got 10 customers all belonging to the same group. So it’s really important to know what is your total exposure to a single group. The other thing is, we always think it’s important that you look not only at the company you’re extending credit to but the one at the top of the tree. So it’s a really good idea, if you’re extending credit to a US business is owned by a German company, you might want to know if that German company is bankrupt, because it could have a waterfall knockdown approach. That’s one, not everybody thinks that there’s one, the other one, which is huge in Europe. And I’m not sure it doesn’t seem to be as huge here is the officers behind the company. Because when you’re evaluating credit, in Europe, what we want to know is we want to know, is that officer involved in other companies today? Are those other companies doing well? Or are those other companies doing badly? Or is that officer being involved in bankrupt companies in the past, so when we present the data to our users, they can see this in the report. And that’s a huge landmine because it tends to repeat, the performance of that officer tends to repeat.
Greg Johnson 3:28
So hierarchies and then the relationship of individuals, which has also become important with everything going on with sanctions and that type of thing. We were talking while we’re outside another one that popped up the other day in a conversation with other credit professionals at another conference with cyber risk. And they were talking to saying, Hey, we heard that there was a breach of some sort, we don’t know what the impact is going to be on the health viability of that company as a result. So that’s super helpful. So second one, as we dive into the data, obviously, we’ve heard in several different presentations, there’s all kinds of data coming at you from all different directions. We live in it every day. And I think we struggled to keep up with it. But maybe just kind of go down the row here and ask you to share some thoughts on maybe one alternative data source that you think is different than that, which we’ve all been using for years from credit apps, and sort of the basic reports that type of thing, but things that can be used going forward and try to keep it simple and important. Yeah,
Mike Flum 4:24
I think I’ll start with Publix since you know, it’s kind of a clitoris monitors known for so I’ll give you guys a little bit through that. And there’s two that I kind of point out. First one would be you know if you have access to, for instance, the management discussion and analysis and a financial filing, looking at that liquidity section of that document, it’s a little bit time intensive, you know, you need to take like 510 minutes to read it. But the same time there’s so much gold in there related to actually dates and times of bankruptcy, and you can see it playing his night. So something to look at from that. The other thing I kind of want to step about is, for instance, in our business for the first score, we actually look at crowdsourcing you guys. Because if enough of you are making determinations in terms of extending credit or pulling back credit, that happens in concert that’s destructive to the working capital that that particular customer, they’re expecting you to finance their inventory. And if you do it in mass to death, now they gotta find some alternative financing, that’s going to come with interest.
Mathew Debbage 5:31
So I’ve got two, the first one is something we call media solutions. So very often the credit leader will say, Google this company to see if you can find out any nasties. And I shouldn’t really say this, but I was Googling Dun and Bradstreet the other day to see if there’s anything nasty on them. And I was on page nine where I found it. So we built this clever algorithm that has something like 150 risk terms, and we monitor this. So we’re searching the web. And we bring back those articles inside the report. The second alternative data, which I think is the greatest data I’ve ever had, in my entire career in this industry, is what we call financial payment data. So we’re extending credit. And we tend to look at the days we on terms we look at that payment data, How late are they? Am I going to get paid on time? Financial payment data is all the big banks and financial institutions like Wells Fargo Bank of America, we can tell you how much credit a business has available to them, what’s their credit, total credit line. So if you’re looking at a report, and it says this company pays 50 days late, you look at this data and will tell you, they’ve got $10 million of credit available to them. And they’ve only use half a million. So it’s another way of thinking, they’ve got the money to pay you. And it’s great for collection as well. Because when you’re collecting, you say I want to be there, you’ve got nine and a half million here. Why can’t you pay me just two? Got it. But we’ve been on conferences where this is been three days on this subject. So we’re up against the clock
Jerry Flum 7:24
sunrise. My insight on some new stuff would be sort of what Mike was talking about. And that is, the trade that credit managers extend into the corporate world is three to four times or three times bigger than bank extension of debt to corporations. So the bank, the credit managers or corporations, what they’re doing, if they’re willing to extend tray is an absolutely critical function. Because remember, for the most part, you’re extending trade with no expense for the company. And so it’s a very important thing to them. And so what we do is at our company, we monitor by the clicks. In other words, when credit managers get upset with a company, that’s a public company, our database goes, depth all the way down to very, very precise measurements of what’s going on there. And so over a 15 years of looking at the clicks on the data that we have, the patterns of it, are absolutely predictable whether you guys are going to stop issuing trade credit, as I said to you, in the early part, you represent three to four times more money going into corporations than banks do. And everybody looks at that, excuse me, everybody looks at banks. But you guys are the power movers. And you want to know what you’re doing. So I’m telling you pay attention on our first score we have, we measure that and it’s measured every night electronically show it’s up to the minute. So that’s my suggestion.
Greg Johnson 9:22
Interesting. So you can see there’s a lot of different flavours. One of the others that comes up a lot these days is we mentioned the cyber data ESG data, what are the ESG scores becoming more popular conversation and if you’re seeing that, but that’s when we talked about and then one of my favourites, I can’t miss the opportunity to talk about spend data in the early warning signals that come from changes in spend. If you’re watching the trends and spend looking at clicks and it’s this is all about that trending and kind of what Sanjay was talking about earlier, but you know, you watch that spend, you can see the early warning signs because they’re going to stop spending on less important things before they’re going to start slowing their payments. So we’ve talked to about data, we’re talking about alternative data. I think what we were all talking about also before, and I’ll speak on behalf of the crowd here, the panel was the notion of analytics. And one of the things we try to do as every one of our companies is to take that raw data that we’ve got, and bring that to you in the form of something that’s less raw, whether it be a score, or a flag, or an alert, something like that. That’s actionable. Because ultimately, to gain efficiencies for you all, be able to bring that into a platform like HighRadius, so that your analysts can understand it, and not have to take just the raw data, we deal with the raw data all day long, right. But then I guess the other piece of feedback we always like is one of the things you want to see we can bring you the ideas, but then also, you know, things that we can do to create automation, or apply analytics to that raw data to make efficiency more achievable. And to be able to populate the screens in the dashboards and things like HighRadius. So kind of an important one on that. So we’ve got the electrons. This data speak for data. Nobody laughed. It’s a tough crowd, I guess. And that’s all I got, you can see why I’m a data guy, I guess so. So we got the electrons, we got the analytics. So I’m gonna actually kind of bop ahead and say, if we had one thing, and this isn’t that 18-minute rule if you had one thing that you would give as a piece of advice, as to what everybody could think about to empower them going forward, what would be the one piece of advice that you’d share with them as to things that you’re seeing in the world of data and analytics, and automation to drive efficiency and to improve their decisions?
Mike Flum 11:38
I think it takes a little bit of nuance to think about big data is really great when you’re talking about the design of like ML-based models, things like that, where you just need to feed it a lot of examples. But one of the things that I struggle with a lot in some of the client conversations that I have is the idea of score carding as a way of trying to get a mosaic approach for what risk looks like. And the problem that I see with that is that a lot of times the way scorecards are combined is you take all of these various different scores or, you know, data inputs, and you essentially just combine them into an individual analytic to say the rating is x. And the problem is, in most of these cases, we all spend a lot of time and money optimizing whatever you’re taking in, and it’s specifically figuring out what those weightings are to give you the best predict, you know, predictivity of bankruptcy risk, or default risk. And so when you combine, for instance, something like, in our case, the first score and the Altman Z score, you guys are all probably aware of it, that’s now double counting financials. Right. So you’ve actually taken something that’s very predictive and made it less predicted by overweighting. A particular factor. So when you start thinking about big data, and some of the pitfalls and big data, you really need to understand correlations of data, because you’re oftentimes oversampling a specific type of thing. And that’s a real big pitfall. Because it really hurts your ability to predict whether or not you can collect, whether or not you should be underwriting at that level, or what terms you should be setting.
Mathew Debbage 13:10
Well, my advice is the USA data, in some ways is the worst in the world. And in some ways is the best in the world. The reason it’s the best in the world, is people are sharing ledger data. So there’s more insights into payment information. Now, without payment information inside the US, there is no data, because we’re blessed in Europe and many other places in the world with Financials on companies like these guys are the publicly traded companies. If you share sometimes it’s a bit of a nervous thing, because this is your crown jewels. But if you’re able to share the insight we can give you that way we can help you make more Yes. Is the correct? Yes. Is the correct knows the correct refers? So please share, because I’ve got a feeling things might get a bit nasty over the next 12 months and we need more. You know, we haven’t seen the impact is unbelievable. I haven’t we haven’t even seen a huge deterioration in payments yet. It’s coming.
Jerry Flum 14:25
Jerry, it’s coming. Look, that’s an interesting piece of advice. It’s coming. I can tell you when I look out in the world today, and I see debt levels where they are at government at corporate, at non-financial corporations. There’s a tidal wave coming and I don’t think you have to be too sophisticated about man, it’s in front of you. And the question everybody always asks like, when is it going to happen? And I would suggest to you that don’t waste your time. Mr. Net, it’s no longer when it’s going to happen. So what are you doing now to be prepared for when this happens because it will be the biggest in your lifetime that you will ever see again, and it will not last six months, it will not last three months, it will have to correct 15 to 20 years of an over-indebtedness on the part of our societies, all of our societies. So I think that’s the key takeaway. second takeaway, I would say that’s different. When you analyze public companies, as opposed to private companies, it’s a very different game. CFOs of most companies understand that most people are looking at the universal because there’s hundreds of 1000s or millions of private companies. And therefore credit people are we are required to look at payment data because that’s all they’ve got. So once the score is on payment, data started to be used universally. CFOs understood that they needed to game the system. They’re not trying to hurt you, and they’re not trying to do something illegal, but they need to present a picture that will influence a payment score a paid X type score, since everybody’s using it, you need to gain how you pay so that you can influence the score. So when you’re looking at public companies understand that you’re looking at scores that CFOs are going to gain, we collect two and a half trillion dollars with the trade payment data. So we analyze it, I am telling you, it’s a gained system, not because they’re bad, they’re doing it because that’s their job. So pay attention to what kind of company you’re looking at, and how you want to analyze it or have it analyzed for you. Public companies are very different. And I can tell you, in our data, we see 60% to 70% when we analyze the trade payable data on corporations coming from public companies. They’re huge, they have hundreds of divisions and subsidiaries. So they represent a lot of business. And I’m just suggesting look at them differently.
Greg Johnson 17:40
I’m just gonna build off that I was gonna say my suggestion is monitor, monitor your portfolio. In North America, somewhere between six and 700,000. Businesses coming go out of business every year. Right? That’s an SBA Small Business Association number that says 5% of your portfolio is at risk at any given time. I was you’re talking about gaming the system I was on, I admitted I tick tock from time to time, I have two dogs, and they’re on tick tock with me. And I don’t know, they must have heard me and that I was doing credit stuff. And a kid was on there. And he talked about how you could get a Mercedes in the name of your business with your business credit. And he proceeded to name off for companies to go get trade credit with and buy one thing from them, wait 90 days, and then take your application to Mercedes Benz credit. Right? That’s what we’re up against. So you’re not going to capture everything, there’s no net, that’s going to be fine enough because we all know, the sales organization is going to drive us to say yes, in a lot of cases, right? Nobody’s been told to just ship it from the sales team right? Now. I doubt it. So you’re gonna have to say yes. So it’s going to be that monitoring, it’s going to be looking at the media, looking at all the other scores and things, and that’s where we’ve got to dictate the responsibility on our sides. And I think we all believe in that is delivering to you all the things that will alert and give you the ability to monitor for their partners like HighRadius who can present that in a fashion and make it actionable because it’s a lot for everybody to look at every day. So with that, I think we’re at time for our 18 minutes. We did pretty well on that team. So nice job and
Anchor 19:17
sound good. Okay, questions. If you’ve been in any of my sessions, you know, I have gifts for people ask questions, so. Okay.
Audience 19:27
Hi, Molly from serious thank you for your insights. I’m wondering, are you working on any type of equation like z factor and correlation, thinking about where we’re headed next?
Jerry Flum 19:42
I think we’re heading to hell. I wish I could tell you that when
Anchor 19:49
Newsday credit and no I’m looking,
Mathew Debbage 19:52
we hold on it. Horrible bad news. It’s horrible to give back.
Jerry Flum 19:59
Yeah, but We’ve had 20 years of declining interest rates and debt has gone up to skyrocket levels. But nothing in the world is better than going into debt. Nothing.
Anchor 20:11
My study is linear with you about you, you don’t need like eight variables, it takes very few variables. But how do you look at a variable for what’s to come? That data doesn’t exist today?
Mike Flum 20:22
What? Let me just anecdotally answer your first, right. So one of the case examples that I look at that I think is really telling for interest rate concern, right? You look at Home Depot, for instance, a business that did very, very well, in the in, in COVID times I mean, who else is doing something with your house right? Six months ago, and Greg can probably tell you this even better than I can because I think Moody’s was the radar for it. But anyway, they wrote a 1.2 $5,000,000,000 10-year bond. That was that I think, 1.85%, six months later, they came back to that exact same market floated 1.2 $5,000,000,000.10 year bond, do you know what the interest rate they got was 387, or 385. So in six months, went up 76%, for a business that, you know, as far as corporate America is concerned, is about as highly rated as you could get. So when I look at that, my big concern, where I see it going, is that you have an interest rate environment going up, you have an enormous amount of businesses that typically fall into that zombie category of not being able to cover their interest expenses. And a lot of them actually have a lot of short-term debt already. Right. So you combine all those things, there’s a maturity wall that comes into these businesses, right. And if they can’t refinance that, or if they refinance that at a higher rate, and they already can’t cover their interest expenses. That’s a really bad scenario. So as far as data is concerned, I mean, I use the scores as my first pass. But when I see a business that’s like frisk red zone, for instance, and I want to go in and win that conversation with sales, I go immediately to that I look at trailing 12-month interest coverage ratio, and I look at exposure to short term debt. Because if I can correlate those two things I know in the next nine months, they have a huge financing problem.
Mike Flum 22:26
So yeah, yeah, I mean, so that’s the thing, you could look at it from a free cash flow perspective. But when you get into free cash flow, I think you guys will be very surprised with how businesses are performing.
Greg Johnson 22:38
Now. So I’ll just give it a little different view, which goes down to the weeds of the small, small businesses where you don’t have necessarily financials or you don’t have debt ratings, right. Moody’s, it’s having come from Quarteira. Now being at Moody’s, and there’s all these other tools like the economist in the industry level analysis that they’re doing, those are the things that we’re building into models going forward to create new models afford a predicted default ratios or rates, predicted rate, predictive default rates. So using that, because that’s really the only forward-looking type of thing you can do with the small businesses when you have the good data to be able to do it, then you can’t beat financial data in the rough facts, because the facts are the facts, right? He just articulated that very clearly. But we got to be able to look at that population of, you know, literally millions of companies that are small that don’t have that data. So it’s hard to get everybody’s trying to push in that direction now.
Audience 23:33
I heard earlier ESG data being used. There’s a lot that’s being disclosed. It’s not really consistent. What do you find is predictable? Predictive, sorry.
Greg Johnson 23:46
Yeah, so the getting the ESG data is the hardest part, understanding the depth of the data, and really the coverage. So it comes down to the places that you’re going, depending on whether it is the environmental, the social, or the governance-related data. And each one has a very different Well, in which you have to be able to dig to get the relevant information. It doesn’t, it doesn’t, it’s not enough to be able to generalize and say, okay, at an industry level, here’s what we see. Because that can be wildly different from one business to the next. So the ability to use things like we’re talking about with credit safe and to be able to do analysis of, of written information and reports that are available publicly information, available information in news and media, that type of thing, or reports that are published about companies is important to get. But it’s it’s a lot of detail, we can talk for quite a bit about it. But is it’s a big piece of where we’re going to be able to invest and trying to find best of breed data sources to be able to fill each one of those buckets, but it’s a conversation that we’re getting hit with on an on a daily basis right now for sure. Yeah. predictiveness is the hardest part though because otherwise soft stuff and I’m not big on soft or self-reported. That’s not my thing on facts. Give me the facts. Right. So, good question. I think that’s
Mike Flum 25:09
hard, though to like, that’s really hard to do in terms of productivity, because we just don’t have enough data set. Right? You need trend in order for that to be usable, because you need an output vector to match against. I mean, look at last year, I think the at least the US public company bankruptcy rate was like 30 bips the long run average on that is one to 1.2% at standard deviations apart.
Greg Johnson 25:38
It’s more like it’s more around, how are they doing with it right now is really where it goes, you know, what are they? Exactly?
Mike Flum 25:43
It’s totally useful. I don’t think I should discount it. I just think it’s really hard to use for modeling because we just don’t have enough trend analysis to know, does ESG and having a positive ESG actually relate to a better position for your business? Are you spending dollars upfront? Yeah, right now, it’s all about how you allocate your spend, right? Where are you spending it? And is that actually creating a more stable business? Certainly, it is. from a social perspective, I think that’s clear. But that doesn’t necessarily Jive always with Financials. So something to keep in mind,
Jerry Flum 26:16
I feel very differently, I think we’re on the precipice of a very difficult time. And so I think it takes super, super concentration on the most critical variable that faces a corporation in the United States or around the world. And what that is over-indebtedness, and rising interest rates, the confluence of huge debt, and rising interest rates will be the most significant catastrophe that we have faced in 50 to 80 years. And I would suggest you pay attention to the very basics of survival in corporate world in the United States, and certainly overseas. And that’s the balance sheet, we are in a balance sheet crisis going forward. And that means you need to pay attention to cash flow, you need to pay attention to the flow of how they have to refinance, you have to pay attention to interest rate, incremental interest costs, to the marginal profitability of corporations. And the third thing I want to say to you, as somebody who’s studied this for I guess, 30 or 40 years, I am telling you that when the large industries have a huge amount of companies within the industry, over-indebted, as the weaker companies go out of business, they will cut their prices to $1 over cash flow. Okay, and you can’t fault them for doing it, they’re trying to stave off going out of business, that means prices will come down for every single company in that industry. That means margins are coming down. And that means that interest expense, which is fixed, is going to be difficult as hell, prices are going to contract. And that means balance sheets, I couldn’t stay focused. And remember that you guys need to pay attention to what other people are doing. Or other competitors. If your guys come in with a super big order. Let’s try and find out why they got the big order. Did that scale? Did the sales skills automatically just go up? Or are other companies that claiming to shell to that customer? So there is an override and I, I am for all kinds of subjective evaluations are looking at corporations. Now is just not the time to lead with
Greg Johnson 29:15
the industry level health as part of it sounds like we’re gonna say industry level health is pretty important to evaluate what’s going on more broadly, the big guys and small guys and everybody else,
Jerry Flum 29:25
I face it every day or I’m speaking to senior guys and they say, Look, we’re not as leveraged as the other guys. And we’re a great run company. And, look, all I can say to you is I’m not worried about you. I’m worried about the guys you compete with because they look you know, Warren Buffett said it the best way I’m kind of quoting him a little out of context. And you said you have to be in a hall of fame of crappy business managers to run a debt-free company into bankruptcy. Okay, you have to be in the Hall of Fame of a crappy manager to run a debt-free company into bankruptcy. The converse of that is, the more debt you have, it doesn’t matter how damn smart you are. Okay, that game is over, you’ve already indebted the company. So you have to pay attention to everybody. And that’s, you know, in our company, we look at a lot of industry and peer review, and we ranked your competitors are going to be problems. So, that’s my advice to you. What is worth? Do you have to be in a hall of fame of a crappy manager to run a debt-free company into bankruptcy? The converse of that is, the more debt you have, it doesn’t matter how damn smart you are. Okay, that game is over. You’ve already indebted the company. So you have to pay attention to everybody. And that’s, you know, in our company, we look at a lot of industry and peer review, and we ranked your competitors are going to be problems. So, that’s my advice to you. What is worth? Thank you again.
