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The CU2.0 Podcast
This podcast explores contemporary, critical thinking and issues impacting the nation's credit unions. What do they need to be doing to not just survive but prosper?
The CU2.0 Podcast
CU 2.0 Podcast Episode 376 JUDI.AI's Gord Baizley on Supercharging Small Business Lending
About 45 credit unions are customers of JUDI.AI and they are drawn by the company’s simple promise: Eliminate friction in business lending.
There is money to be made serving small businesses and JUDI.AI has the formula, says Gord Baizley, the company’s CEO.
A key is automating a lot of the process and that’s JUDI.AI’s business.
Here’s why the company exists: “Small businesses are the backbone of our economy, but 40-50% of small businesses rank access to capital as their top challenge. At JUDI, we’re transforming small business dreams into vibrant communities by increasing access to capital.”
That’s a big promise but, says Baizley, the company has had very little churn among credit unions who sign up. That’s because they believe they are getting value and also that in fact they are finding ways to serve their communities’ small businesses.
Just about every credit union, certainly all bigger than $500 million in assets, dreams about making small business lending a bigger slice of their portfolio.
Baizley insists that dream can be reality. On the show he tells how.
Listen up.
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Welcome to the CU2.0 podcast.
SPEAKER_00:Hi, and welcome to the CU2.0 podcast with big new ideas about credit unions and conversations about innovative technology with credit union and fintech leaders. This podcast is brought to you by Quillo, the real-time loan syndication network for credit unions, and by your host, long-time credit union and financial technology journalist Robert McGarvey. And now the CU 2.0 podcast with Robert McGarvey.
SPEAKER_01:About 45 credit unions are customers of Judy.ai and they're drawn by the company's simple promise. Eliminate friction in business lending. There's money to be made stirring small businesses in. Quote, small businesses are the backbone of our economy. But 40 to 50 percent of small businesses rank access to capital as their chief challenge. At Judy, we're transforming small business dreams into vibrant communities by increasing access to capital. That's a big promise. But since basically the company has had very, very little turn among credit unions who signed up. That's because they believe they're getting value. And also, in fact, they're finding ways to serve the community's small business. Just about every credit unit, certainly all bigger than$500 million in assets, dreams about making small business, lending them bigger slides for their portfolio. Credit unions are finding that they can do it. And some of those credit unions as are as small as maybe$25 million in assets. And historically, as I'm sure you know, small business lending has been something credit unions have wanted to do, but they haven't done it for many reasons. One of which is that it's not usually profitable for them because the amounts in their lending are too small to justify the labor that goes into betting the app loan application to simplify matters. I mean, and that's true with big banks too. If I walk in the chase and say, hey, I'd like you to give my small business a$50,000 loan, my banker there would say, um, we'll give you a personal loan, but not your business.
SPEAKER_02:Yeah. And I mean, it you're right, it's not just credit unions, it's the broader market. And if you look at the you know, sentiment data out of any survey of small businesses, they'll say they're underserved from a banking perspective and a credit perspective in particular. It's just a hard segment to serve. And so what's happened is you know, fintech lenders have stepped in to fill that void. The problem is they're not deposit-taking institutions, so their cost of capital is pretty high, and so they have to pass that along. And next thing you know, your you know, your APRs are 30, 40 percent.
SPEAKER_01:Yeah, I talked with a guy uh a couple of years ago who does just small business lending, and he told me traditional financial institutions we're kind of dead at the starting block because they they ask for the wrong data. Um what's your Dun and Bradstreet writing? My what? And furthermore, yes, the Dunham Bradstreet doesn't know who this company is. Two, what's what's your FICO score? Well, some of them are having money problems, and their FICO score is really taking a tumble. So he said, all I look at is cash flow. Right, exactly. And he I assume his interest rate, he wasn't specific, but it was over 20, significantly over 20 percent.
SPEAKER_02:Yeah, and that's that's the the fintech lenders sort of figured this out uh uh a while back. And we actually we were born out of an in uh a fintech lender ourselves and then developed a platform and spun out a separate business for for that business. But exactly what we learned along the way is that cash flow was really the the the best predictor of of what's going on and and actually most recent cash flow is really important. So um, you know, the we look at 12 months of cash flow data, and I think that's all this guy wanted was 12 months.
SPEAKER_01:If he had 24, he might look at it. But yeah, but his main concern was if I lend you this money, can you make the monthly payments? And the cash flow told him yes or no.
SPEAKER_02:Well, and there are some fintech lenders that will lend on the back of only three months of cash flow data. Whoa, yeah, and and we've even seen it in our data that you know, months one to three are much more predictive than months nine to twelve from a from a wait a minute though.
SPEAKER_01:If I open the right kind of store uh and I give you cash flow data for October, November, December, I might have zero cash flow in January because I'm selling Christmas gifts, you know.
SPEAKER_02:It's uh so yeah, and and and and I'm speaking in general out generalities across the small business population. Obviously, there's seasonality in some businesses, but but for the most part, uh recent data is more predictive than old data.
SPEAKER_01:Um sure.
SPEAKER_02:That's uh and it's pretty acute actually um across the general population of small businesses.
SPEAKER_01:I mean, that's that's essentially why I really don't like FICO scores as a measure of much of anything except a pretty good picture of my past behavior as a credit card user. But I don't think it tells you a thing about my future behavior.
SPEAKER_02:Yeah, I mean, I think you know, a certain uh a certain baseline uh uh of a FICO score will tell you what kind of a person you're dealing with, and are they likely to you know completely screw up or or even worse, you know, defraud you so you get a sort of sort of a baseline character perspective out of that, I guess. Um and then and then from there though, you really want to know how their business is doing in in real time.
SPEAKER_01:Now, how many credit union customers do you have? And how many US-based credit unions do you have?
SPEAKER_02:Yeah, we're working with uh I think we're creeping up towards 45 customers.
SPEAKER_01:Uh that that's outstanding. How how long has it taken you to get 45?
SPEAKER_02:Yeah, we launched, so our first customer um we was Van City Credit Union, so the largest credit union in Canada. Um, we launched with them in uh May of 2017. So that was that was when the first application went through our first credit union customer. Um, and so that's uh you know eight years ago now um that we've been doing this and uh adding them steadily. We we sort of got into the US market a couple of years ago. That's been going well. We're I think up to 18 customers in the US and uh more coming on, obviously, lots of potential there. But um, we really, to your point, we've the credit unions in both Canada and US, and they're very similar, have historically not done a lot of small business lending for all of the usual reasons. It's expensive and unprofitable. And um uh so they've migrated, you know, they've always focused on CRE to the extent they've done commercial lending, but they are we we're really noticing a pattern now where they want to get into this. They know they should serve their members in this segment, huge important segment of the economy. And so they're they're starting to run at it, uh, which has been fun for us.
SPEAKER_01:What's the size range approximately of your US credit units?
SPEAKER_02:Yeah, so we've got so we work with um uh uh through through a couple of CUSOs, we worked with some very small credit unions, uh, as low as 25 million in assets. Um, and then uh like I say, our largest client is 30 billion in assets, and in there's a we have a couple of those in Canada and and pretty much everywhere in between. Um uh we do sort of notice that sort of 500 million in assets and up is where uh if you're not going through a CUSO, where it where it kind of works, where they can actually um absorb the cost and execute uh on a program that that makes sense. So that's a kind of a threshold that we focus on. But um if smaller ones come to us, we certainly will work with them and we'll uh sometimes suggest that we pull in a CUSO to work with them and help them.
SPEAKER_01:Now, remind me, my my memory tells me that you know the US has approximately 6,000 credit units, Canada has approximately six. I mean, I exaggerate, but yeah, Canada has really big credit units, right?
SPEAKER_02:Yeah, we're so yeah, we're um about 250 credit unions in Canada, you know, and and so um 10% of the population. So if you were to sort of do a linear extrapolation, we should have um you there should be 2,500 in the US to be equivalent, and there's at least double that or something like double that. So yeah, you're right, we're less fragmented and generally have larger credit unions um here uh and fewer targets for us. But uh so it's a bit of a different dynamic.
SPEAKER_01:How how does the QZO come into the picture when you're serving a credit union through a QZO?
SPEAKER_02:Yeah, so some of the credit unions, uh because as you say, they haven't historically done a lot of commercial lending and certainly smaller C and I lending, some of them maybe don't have the expertise to do the underwriting or the servicing or the reviews. And so um they can outsource some or all of that process to uh uh to a CUSO. And so where we can partner with a CUSO and bring both technology and the expertise and services to the table, it enables someone to get up and running very quickly without building out a whole department.
SPEAKER_01:So take tell me, what do you bring to the table and what does the credit union have to bring to the table, either on its own or through a CUSO?
SPEAKER_02:Yeah, so we bring the technology and a little bit of advice around how to configure the technology for um a program based on whatever the risk and business objectives are of the of the credit union. Um and we help them through that journey. But but what we don't do is we don't do underwriting, um, we don't write credit policies, uh, we don't do annual reviews, um, but we can provide the technology to enable all of that. So uh they either need um people internally that are capable of that and that have the capacity. That's another thing. Sometimes it's it's capability, sometimes it's capacity. Um, and if they don't have it internally, then they then they need a CUSO, and there are several around that provide those services.
SPEAKER_01:So your technology automates the lending process. Yeah, yeah. So it does a few things. And so in in the in the pandemic era, and there was a lot of government money to lend in uh the US, government backed loans. Uh the big banks jumped on that. Like Wells Fargo did a lot of those loans. When I investigated, it's it's everything was automated. I don't know what the dollar amount was, was their maximum, but say it was 100 grand. Anything under that was gonna be automated. No human being would touch the application. Credit unions struggled with that, they didn't have the technology, I don't think.
SPEAKER_02:Yeah, and it's interesting, like and in Canada had a similar program too, so the dynamics were very similar. And um, you needed to automate it. There was so much volume coming, but but it was really workflow, not underwriting automation, you know, because there wasn't really underwriting, like they were right.
SPEAKER_01:There was essentially no, but again, it's how much labor can you afford to put into this twenty thousand dollar loan? Yeah, very little, basically.
SPEAKER_02:Yeah, no, we've had uh had uh people say to us like once we've once we've touched the file twice, we've lost money.
SPEAKER_01:Yeah. So uh absolutely it's they they'd much rather do a car loan for thirty thousand dollars. Yeah.
SPEAKER_02:So the the flip side is that um, although they're small amounts, there tends to be pretty good margin in the segment um uh for a number of reasons. And so if you can figure out how to control the cost of delivery and do it at scale, it can actually, like some of our clients, this is their most profitable segment. So um once you get to that point, it it's it's very worthwhile.
SPEAKER_01:Now, you don't, I'm assuming you don't provide marketing advice to the credit union. In other words, here's how you go after small business lots, A, B, C, and D.
SPEAKER_02:Yeah, we actually do a few things on that front. Um, so so um the the big thing that we've noticed, um I always say, you know, if you build it, they won't come. Like you can't just stand up a platform and expect that you're gonna get applications all of a sudden. So you do have to activate it. And and one of the most successful ways to activate it is to actually do pre-qualifications of your members. So most credit unions are sitting on a few thousand uh business members um and and they're sitting on all their account data, that cash flow data that is very predictive. And we can go through that and give them a picture of who they could make offers to. And the the conversion rates and the uptake from small businesses has been incredible on those types of exercises, I think, for two reasons. One, um, there's a high degree of trust between the business members and the credit union, and two, business members, unlike consumers, aren't used to getting these kinds of offers. And so we've had um we had one client do do one of these Libro credit union in in Ontario and Canada, and they had a 30% conversion rate on offers made out of one campaign, uh, just to give you a feel for how successful that was. But again, you do have to be proactive. Pre-quall is one way to do it. You can do digital email campaigns to your members, and of course, you can get out and do you know more traditional digital marketing beyond your membership base. What we've seen with the credit unions is they have so much low-hanging fruit in their business member base that they haven't had to go outside yet. They can focus on that. The other area that's also interesting is um, and we've got a partner, uh, Fingle out of Colorado, that can do some analysis on this, uh, but but they can comb through uh a credit union's consumer accounts and predict which ones are uh in all likelihood running a business out of those accounts. And it's usually somewhere around 10% of your consumer members are are running a business out of the account. So um there's an opportunity to sort of migrate those over to business services.
SPEAKER_01:That's that's interesting. You know, credit unions in the US is for some years now have technology that lets them, and it happened to me with my credit union. I didn't have a credit card. They sent me an email or a letter saying, hey, you know, what we we we really want to give you this credit, this credit card, like a$20,000 limit. There's no fee. Do you want it? I said, huh? Yeah, I guess so. But but they're they're cut they're accustomed to doing that. So this is just doing that same thing with with small business members.
SPEAKER_02:It is, and and and it's easy on the consumer side because if you have a bureau score, you're comfortable doing it on the back of that, typically. Um, but it with a small business, that doesn't quite cut it per your previous points that you were making around that. So you have to look into the cash flow and uh and be able to make sense of the cash flow in the in the operating account to decide whether that's a an offer you can make.
SPEAKER_01:I I don't think my credit union even had a Euro score when they offered me that. It's uh I think they just they just looked at um my accounts to balance in them, et cetera. And so by heavens, he's paying$4,000 a month to American Express. Why don't we get a piece of this?
SPEAKER_02:Yeah, there could be some of that. I know a lot of them um uh for compliance reasons at least do soft polls on their on their consumer members. So a lot of them will have that that on file.
SPEAKER_01:And I could be a soft poll that I never would have seen. That's that's true. That's uh and how long does it take a credit union? A credit union calls you up when they hear this podcast and they say, we want to get started on this. Now that won't happen. They're probably gonna ask you to convince them to get started on it. But we'll we'll just imagine that. It's uh how long does the process take?
SPEAKER_02:Yeah, so we usually guide people to sort of allow for eight to 12 weeks to get live. We've done them in as little as four weeks. They've also gone longer, depending on some uh uh some of the choices and dynamics in the account. But um, if we keep it simple and we really want to just get up with uh uh a basic implementation, it can be pretty quick. And if in fact, if someone came to us and said we need to be live in a week, we we could, you know, in theory, uh get everybody uh aligned very quickly and be live that quick. So it it is um it it doesn't have to be a massive project. You know, I think people think about core conversions or massive LOS implementations and they get scared off, but this this problem can be actually solved quite quickly.
SPEAKER_01:Do you need core system access?
SPEAKER_02:You don't need it out of the gate. No, so um the way we can uh access the cash flow data uh is through the account aggregators in the market. So there's a bunch of them out there that you know, PLAD, et cetera. We use Yodly um uh as our primary access point. And the reason we do that is um A, you don't need to integrate out of the out of the gate, which uh expedites the process, but B, you can also access accounts at you know other institutions. And about 20% of the applications we receive have accounts, you know, multiple accounts at multiple institutions.
SPEAKER_01:And increasingly more and more of us are familiar with Plat at least. Yeah.
SPEAKER_02:Yeah, it's a it's a journey, and I always always say it's you know, open banking and quotations, we're not there yet, but there are increase an increasing number of open banking-like, you know, API connections into these institutions that are, you know, uh one day this this technology will be ubiquitous and hopefully on a standard protocol.
SPEAKER_01:And what's your fee structure?
SPEAKER_02:Yeah, so we charge um uh a subscription fee for the platform that that varies by size of credit union, and then we charge a fee per completed loan application. Um, so anything that we score basically, we we charge for. And in that in that fee, we would absorb the cost of the Bureau scores and the data connections. And so it's fully loaded, the DocuSign envelope for the loan agreements.
SPEAKER_01:Um what's what's a range for the the monthly fee?
SPEAKER_02:Yeah, the the range is uh as low as 4,000 a month and as high as 30,000 a month for the the massive credit unions and uh everywhere in between, and then the application fees$140 for the the completed and what's what staffing specifically does the credit union need on its end to make this work? Yeah, we sort of we we recommend like three primary stakeholders in a successful implementation. And the first one is some sort of an executive sponsor that's really going to make sure that there's you know strategic prioritization at the top of the organization. And if you have that, that that's a key marker of success. Um, the second one would be um a forward-thinking subject matter expert around lending and commercial lending that maybe wants to make a change. So somebody that's comfortable with technology and changing process, and that can that person would be the driver. And then a project manager just to get it going and they don't have to stay with it, you know, much beyond the implementation, but having somebody just coordinate with you know marketing and legal and um and credit risk, et cetera, to make sure that it gets off the ground. And it's not a ton of work uh with all of those stakeholders, but they do need to be informed at least.
SPEAKER_01:Have you had customers who are doing this and then decide to quit? And if so, why?
SPEAKER_02:Yeah, good question. We've had um to the extent we've had churn, um, we had a couple that used it for uh the SIBA program in Canada, um, which was like the PP program and the PPP program in the US, and then they didn't continue on. Uh, they tended to be the smaller credit unions that didn't have the resources to do it. So that that's really the the biggest blocker that we've seen is if you just don't have the strategic prioritization and the resources to to move forward. Um, and so that's where we've sort of noticed there's a line there at around 500 million in assets, where below that you may need the help of a CUSO to push forward.
SPEAKER_01:I've often asked credit union CEOs, why don't you have blah, blah, blah? And the answer often in many cases is I'd love to, but I don't have the staff. And these these are smaller credit units, these are not credit units, and certainly not ones over a billion dollars in assets. Although I'll tell you, in the last couple of months, twice now, CEOs of billion-dollar credit units have referred to themselves as running a small credit unit. Twice. Two different guys. So billions now small. Okay.
SPEAKER_02:Yeah, the landscape's changing for sure. And um, yeah, those those resources are are critical. And if you don't have them, it won't move forward. And one of the challenges that we see quite frequently is, you know, like you say, the legacy, sort of the heritage of of credit unions is on the consumer side typically. So so these the commercial side of the house tends to have it struggle a little more to get the resources for these kinds of projects to to grow that side. So a bit of a chicken and egg.
SPEAKER_01:That said, um many credit unions recognize that basically they're forcing their customer out, their member out the door. Yeah, if I start getting my business loans from Wells Fargo uh or a fintech, what what makes you think I'm gonna stay around as a credit union member for very long? And what credit unions don't like to analyze a heck of a lot is share of wallet. And a generation ago, they often had a hundred percent share of wallet from many of their members. That's uncommon today. Um my credit union has maybe 15% of my wallet, maybe it's uh and uh and I'm perfectly happy with it.
SPEAKER_02:Well, and a couple of things to that point. One is um if you look at the if you deconstruct the data, about 25% of U.S. households have a small business attached to them. Um, so it's important to be able to serve those small businesses because a big chunk of your population is going to need that service. Uh, secondly, and and you know, this has come to light with some of our more successful clients like Van City, that's now been doing this for eight years and really leaned into it. You know, they're now doing, they've done in they've had months where they've done 500 applications through our platform. Uh, but they treat it as a very strategic segment. They view it because of that sort of high incidence rate in the population. Uh, but also the the the I guess the the sort of emotional component to a small business, like if if if you fund someone's small business dream, chances are they're sticking with you and they're probably bringing everything else with them. Um so there's a really strategic component to the relationship out of that segment.
SPEAKER_01:Right. I mean, if you do a small business loan, almost certainly the business will ask for a small business credit card too, eventually, if you have that to offer. Um I mean it's now will your system accommodate gig workers, like a full-time Uber driver, that sort of thing.
SPEAKER_02:The yeah, the where where our system works is it if if the business has a business operating account, if it's a if it's a you know a side business run out of a consumer account, um, we we sort of think of that as a consumer loan. So it's it really needs to have a business operating account. So if that gig worker sets themselves up as a business, we could do it. But if it's sort of a side thing, then it you'd probably treat it as a consumer loan. Does Canada have a lot of gig workers? We do, yeah. I can attest to it personally with my with my DoorDash bill.
SPEAKER_01:Yeah, the US has an increasing number of gig workers, and I know a lot of institutions are kicking around conversationally, how can we better serve these micro businesses? Let's call it not even a small business, but a micro business.
SPEAKER_02:And if you look at the the data in the small business world, you know, our like our platform was underwrite uh and our model extends up to 250,000. But if you look at the data, um, you know, 90% of applications are still under 100,000. Like that is just where the market need is. It is really a lot of really small businesses, typically, you know, five people or less, uh, and and they don't need huge sums of money, which makes it hard.
SPEAKER_01:But typically, what kind of default rate do do you see on the loans?
SPEAKER_02:Yeah, so it varies obviously um you know by credit union because there's different differing populations and different credit policies. So we measure the risk, but we don't tell credit unions how much to take. So they're all doing slightly different things, but in general, they play in the in a similar zone. And what we've seen over the course of time is an average predicted default rate uh uh out of our model based on the policy chosen by the credit unit of around 2%. Um, so far the default rates have been less than that. Um uh so the the actual has been less than predicted uh for a variety of reasons. Um but we do say that you know, believe the model, believe the predictions, build your pricing and your business model around the predictions, and and uh you'll be safe in the long run. So, you know, that we think of this more like um less like a commercial real estate portfolio where you're shooting for a zero percent loss rate and more like a consumer credit card portfolio where you might have a two or three percent loss rate and you're pricing for it.
SPEAKER_01:Yeah, I to me that would be much more logical. Uh the credit union can set its own lending criteria. They can decide, well, we're not going to lend into this sector, for instance. True?
SPEAKER_02:Correct. Yeah. So there's kind of two components in in simple terms for uh to the to the implementation. One is, you know, we we roll out the credit model, which doesn't change by credit union, uh, it produces a probability default. That becomes a rule that the the credit union sets for you know what what what's the threshold for auto approval. And then beyond that, there's a series of configurable business rules uh that the credit union sets and we work through it with them. So you mentioned excluded industries as one, but it could be minimum time in business, it could be um minimum revenue thresholds. There's there's about 25 of them that we look at that um the credit union can consider.
SPEAKER_01:And the the credit union can also determine how many months of cash flow they need.
SPEAKER_02:That's right. Yeah, so um we we our minimum is six, so we we won't underwrite on less than six. But if uh but if they want to say we we we won't underwrite on less than 12 under any circumstance, they can say that.
SPEAKER_01:I know in the US, quite a few the vast majority of credit units wouldn't want to lend a dime on to a cannabis business. But there's also about a hundred or so that really want to lend money to cannabis.
SPEAKER_02:Yeah. Yeah, it's it's funny. I was um we have a couple clients that do, but like you say, most don't. I was just at a at the CUBG conference this week uh uh in San Diego, got back last night, and one of the credit unions I was talking to there was asking me if I knew of any credit unions that would refer out that business to them. So they're quite keen on it.
SPEAKER_01:Oh, yeah, there's a handful of that, and these are these are smart credit unions. They often in some cases they've been asked to get into the business by state government, which wants to get a little bit of the cash out of that business and into banks and credit unions. Yeah, yeah.
SPEAKER_02:It's interesting, and there's some margin in it, I think. So yeah.
SPEAKER_01:So what's what's what's your next step in this business? What's the next evolution?
SPEAKER_02:It's sort of continuing to do two things. Obviously, grow the customer base and the size of our data set, because that's one of our real assets, is just the the fact that we've been doing this for now you know 10 years, including our time as a lender, and we've accumulated a pretty big set of performance data. So we want to keep continue to do that, but also add functionality. So, you know, things like uh we're working on an embedded lending project where you can put uh loan applications inside of different software applications where small businesses live on the internet. Uh, we're we're working on a second look program where we can actually evaluate a board or based on two credit policies. So if they don't pass the credit union policy, um there's an instantaneous uh application of it to the to the second look partner, and and you'll be able to, you know, on the spot be able to tell the small business, hey, we can't help you, but our partner can. Um so we're really trying to get to the point where credit unions can can serve their members uh in a really broadly in terms of you know, if if they don't have a solution, they can say yes somehow.
SPEAKER_01:Has um friction with Canada in the US White House had any impact on your business?
SPEAKER_02:Yeah, very interesting question. Um, I would say no, it hasn't to date. Um, and for I guess a couple of reasons. Um, you know, there's been no tariffs on digital services so far in either direction. There was a little bit of a talk about one about it at one point, but I think the the US is such a net exporter of digital services that that probably won't happen. So that hasn't come come to fruition. Um, so so it hasn't affected us in terms of the ability to work with credit unions. I you know, you could debate whether there's an economic impact happening, which we're you know, maybe seeing in terms of credit quality and application volume. Canada, we've seen a uh a bit of a drop in application volume of late, and that may be related to economic circumstances that. May be related to tariffs, but you know, different people will have different points of view on that.
SPEAKER_01:Might also, at least in the US, be related to what increasingly looks like an inflationary spiral.
SPEAKER_02:Yeah, yeah. And we we haven't seen the change as acute in the US yet as as Canada. Uh, but actually just this week I got an email from uh uh about a client that was noticing uh some some changes in in sort of the the foundations of the economy. So we'll see. It's uh interesting time as always. Well and one of the one of the things that um you know we like about the way we underwrite in our platform is to the extent things are changes are happening in real time, we see the changes to cash flow in real time. Um so and this was true in the pandemic as well, where well that's the beauty of doing cash flow.
SPEAKER_01:Yeah, you know, one thing that happens to a small business, and I've run a small business for most of my life, is if when the economy gets route rocky, suddenly those bills that pay like clockwork on 30 days or 60 days or sometimes 90 days. It's uh so you see like an almost instantaneous impact on your cash flow if you're a small business and the economy begins to go into a recession or every inflation is out of control, etc. It's it's it's so quick. So you you you would be able to see a lot of that data too.
SPEAKER_02:Yeah, that's that's the nice thing about the methodology is when the when the economy is dynamic and in flux, you're you're gonna catch things sooner than you would with tax returns or financial statements or a bureau score, like you say.
SPEAKER_01:Now, how does AI figure into what you do? And it's in the company website addresses then. So what what's the where's AI playing here?
SPEAKER_02:Yeah, there's a couple of spots where we use it. So, and it's all related to the cash flow data. The first is just to make sense of the cash flow data. So you get a bank statement and you have to turn that into something that's legible, basically. So we have a categorization engine um that that transforms a bank statement into a synthetic cash flow statement. So there's some there's some basic AI in there to do that. Uh, and then the main the main application of it is in our credit model itself. So um the way I was explained this is we're we're transitioning from sort of a rules-based underwriting process, which is what you see with scorecards that use, say, financial statement ratios, to a behavioral-based predictive model. So we're looking at the behaviors around cash flow, figuring out how they interact with each other uh in a multi and then producing them a score out of a multivariate model. Um, and so that's a very different approach than saying, you know, if you if you think about the the the move from that rules-based approach, like a common rule would be a 1.25 debt service coverage ratio. Um now that that's been established over the course of time based on intuition and rough experience, but it's not scientific. Why isn't it 1.2 or 1.35 or 1.31? Like the it's just sort of arbitrary, whereas with a predictive model, you can actually figure out what exactly that should be. The second thing is you know, rules or or model variables don't operate in isolation. So there may be you know cases where um a 1.1 debt service coverage ratio is totally fine if you have an 800 credit score or if you keep a million dollars of cash in your account at all times. So there's there's an interplay that that rules don't capture, that behavioral models can capture. And then the last one that I always talk about is what if you just have the wrong rule? Um, and this one's really interesting. So debt service coverage is is fascinating because that's the way that commercial lending's always been done. But with small businesses, they're actually cash out businesses in our experience. And we have lots of data to show this. So they don't run profitably. Um, uh, they they they deliberately commingle personal expenses and conflate capex and dividends. And so so they're they're driving to roughly a break-even point uh uh on a net operating cash flow perspective. And so when you when you apply a traditional commercial lending metric like debt service coverage, it's gonna lead you to say no most of the time. And but that's not necessarily the right answer. And so what the AI can do, and it can look for different variables, different behaviors that are predictive of risk uh beyond the traditional metrics.
SPEAKER_01:And what you're saying makes sense to me. I was a partner in a business, and when you say that, I remember my partner and I would pay ourselves more or less, depending upon the cash flow. And and we wanted to have a certain amount of money kicking around the company accounts, but in the good months, we take more out for ourselves. It's um in a bad month, we take a lot less out. So it's so if you're using that metric, it's not always gonna make a lot of sense with a business that runs like that. And I think a lot of them do run that way.
SPEAKER_02:So and that's why we really, you know, one of the sort of our mantras is to think about small business as a segment. It's not commercial lending and it's not consumer lending, it's it's in the middle, and it's it really is different. It's big enough to be its own segment, and you and it needs a different mindset, it needs different tech, it needs different credit criteria, it needs a different owner inside the credit union, all that kind of stuff. And it's underserved, it's a great opportunity. Yeah, hugely underserved. Um, and and the data shows it all everywhere you look.
SPEAKER_01:And there's all kinds of small businesses. There are farms, for instance. I mean, fewer and fewer, to be honest, that are small businesses, but there's still in parts of the United States, there are a lot of small, small farms that probably have trouble getting loans. It's um, I mean, it's a wonderful opportunity there.
SPEAKER_02:Yeah, there's no question that it's it's a a massively underserved opportunity. Um, one that could, you know, serving it better could have huge impact. Um, there was a study out at McKinsey recently that talked about how um small businesses are about half as productive as larger businesses, and part of the challenge uh there has been they're undercapitalized, so they can't get as productive. And and the punchline in the whole thing was the impact of making those businesses more productive with more capital could could be something like uh to the tune of five to ten percent of GDP in the US. So it's just a an enormous issue for the economy that that uh and if we solve it would have huge impact, but also could be quite profitable. Again, you know, years ago you couldn't do this profitably, but now you can. It actually can be one of your better lines of business.
SPEAKER_01:Yeah, yeah. And for the doubters, we saw exactly this during the pandemic government loans. It was purely automated, streamlined. Yeah, there was no risk because they were all government backed, but nonetheless, it was they could make loans really quickly.
SPEAKER_02:And aside from the workflow that with the technology now and the you know, the models, the AI models, you can you can manage the credit risk quite effectively too without spending day hours and days on a file.
SPEAKER_01:Before we go, think hard about how you can help support this podcast so we can do more interviews with more thoughtful leaders in the credit union world. What we're trying to figure out here in these podcasts is what's next for credit unions. What can they do to really, really, really make a difference in the financial scene? Can't all be mega banks, can it? It's my hope it won't all be mega banks. It's it'll always be a place for credit unions. That's what we're discussing here. To figure out how you can help, get in touch with me. This is RJMegarvey at gmail.com. Robert McGarvey again. That's RJMegarvey at gmail.com. Get in touch, we'll figure out a way that you can help. We need your support, we want your support, we thank you for your support. The CU2.0 Podcast.