Banks Should Partner with Tech, Not Just Fintech [Podcast]

How could a bank benefit from partnering with a restaurant management software company? To start, it would provide access to actionable, industry-specific data and insights that would otherwise be unavailable.

Dallas Wells, our Chief Success Officer, joins us to discuss this and other benefits for banks who choose to partner with tech, not just fintech.

 

Helpful Links

• How NOT to Buy Technology in a Bank - Blog (10 minute read)

Podcast Transcript

Jim Young: Hi, and welcome to The Purposeful Banker, the podcast brought to you by PrecisionLender, where we discuss the biggest topics on the minds of today's best bankers. I'm your host Jim Young, Director of Communications at PrecisionLender. With me in the studio today is Dallas Wells, our Chief Success Officer. Thank you all for joining us.

Unless your bank has its corporate headquarters under a rock, you're aware of all the talk about the growing need and opportunity for banks to partner with fintech companies. The conversation recently seems to have shifted for banks from "Should we fear fintech?" to "How can we work with fintech?" And that's great, but that's not what today's podcast is about. Our podcast is titled Why Banks Should Partner with Tech, Not Just Fintech. What does that mean? To start things off, let's take a look at a restaurant management software company. Dallas, can you give some background on this and explain why in the world a bank would want to partner with a restaurant management company?

Dallas Wells: Yeah. All banks love restaurant loans so much that that's what we want to talk about. There are a whole bunch of examples of this. We picked this one just for that reason. It's an industry that is fraught enough with potential defaults that a lot of banks just say "We don't do restaurant loans." And guess what, there's a whole bunch of restaurants. That's a place where there's lots of potential growth. Those places are getting financing from somewhere. Can your bank be the one to figure out how to do it?

The big trend here that we think there's an opportunity with, and I'm riding on the coattails of Carl with this idea. This is something he's been scribbling on my whiteboard about for two years. I think he's right, and I think there's some early examples of this actually happening, so we thought it was worth talking about. In this case, if you just look for SaaS, software as a service, companies that work with restaurants, there's a whole bunch of them. We don't know anything good or bad about any of those. That's not really the point here. The point is that there are all these vertical SaaS companies that are forming up for just about every industry. For restaurants, for growing crops out in the field, home healthcare companies, life sciences. Veeva was one of the first big vertical SaaS companies. So instead of being like Salesforce where you do software for a whole bunch of different industries, instead you go vertical. You pick one industry, and you basically help people who run those businesses do it better by providing them the type of software that they need.

In this case, if we're talking about restaurant management software, it's software that can help you handle booking reservations. It can help you process credit cards. It can help you order the right amount of ingredients based on what you're making. So it's very specific to your industry. You can kind of put in what's on your menu, and then it starts to learn from that. What kind of volume do we get? There's now data and reporting back of when we offer these things and these specials, here's what kind of bookings we had. You can work on hiring and paying employees through that stuff. It's kind of a one-stop shop to manage your business.

So why does a bank care, right?

Jim Young: Right.

Dallas Wells: If you think about if your bank does happen to do some restaurant loans, I’m sure it’s with the white-knuckle approach, which is even when they look rock-solid and you’ve got experienced operators and you’ve got good collateral and you’ve got good equity in the project there’s a good chance that thing is going to go belly-up. It’s just the reality of the restaurant business.

But if you had access to this kind of data, if you think about the kind of data these restaurant owners are actually using to run and manage this business, from this SaaS product they are now seeing all these trends that they’re making decisions about their business on, what to order, what to offer, how many employees to hire.

And you see trends in real revenue growth and you kind of see it in real time. You don’t see backwards-looking financial statements their accountant provided or some sloppily-made internal financials that you don’t have a lot of faith in anyway. This is much more forward looking. The SaaS company has data that tells them. “based on where things look like they are heading, here’s what we expect to happen in your business.” Again, they are the experts in that vertical. They’re not just working with that restaurant, they are working with tens of thousands of restaurants. So, they get the benefit of “hey, we’ve seen other restaurants like this, based on what is happening this is what we think you should do and what makes sense.” And the bank can see the same thing.

So, the idea is that you get better information, number one, and if you think about a possible partnership here, what better way for the SaaS company to make their product sticky than to, since they already handle all these other things, incorporate banking into that as well.

Jim Young: So it will order your ingredients and will help you get your loan basically?

Dallas Wells: Yeah. It's sort of a "Hey, would you like a loan from Bank X?" You can actually apply right there through the platform. Sucks out the data that the bank now gets in a consistent format. They see the same stuff from the SaaS company all the time. You get metrics to compare against other similar type of restaurants, and you get the guidance and expertise from that software company about what's the real health of this restaurant.

Jim Young: Right. I can imagine the situation. You're looking across that vertical that you know, for example, if you have access to that data, restaurants that are doing 75% capacity have tended to turn this amount of profit within a year or something like that.

Dallas Wells: Exactly.

Jim Young: That you would then have a much better idea of is this a high risk or a low risk loan.

Dallas Wells: It's almost like a pre-screened credit card offer. Only it's a much deeper look. We're not just pulling FICO scores and saying everybody in this zip code with this FICO score, send them this thing in the mail. It is based on these exact types of things that that platform could know and the bank could kind of self-select for. Maybe they have 1,000 customers who fit that profile, and you can then have access to them. From the SaaS company's point of view, they get to offer maybe the world's stickiest product, a commercial loan that ties that customer both to the bank now and also to their platform. They've helped them find financing that for restaurants is tough. Even if you are very good, if you're a successful one, you can go to a lot of banks, and they'll say "I'm sorry. It's a restaurant. We don't do those. Or if we do, we're going to put you through the third degree here to really make it happen, and it's going to take a long time."

Jim Young: I see. So actually, in that situation, their ability to offer up their restaurant data is at least going to make the process quicker for you.

Dallas Wells: Yes.

Jim Young: Because if you're not performing, then you're going to get rejected, but at least because the bank then has access to that data, they can give you an answer faster one way or another.

Dallas Wells: Yeah. If you talk to somebody who owns and is probably helping to operate a restaurant, they don't exactly have a lot of free hours in the day to go shopping around for bank products. So they're not all that price sensitive necessarily. They are time and convenience sensitive. So you can close that gap for them. You can say "Here is one bank or three banks," however you set that up, to say "Here's some options for you." So it's kind of a ready-made customer base for the bank. It's a ready-made product for the SaaS company. It's a concept that, I think, makes a lot of sense.

Jim Young: You just touched something I was just about to ask. Would this potentially restrict competition? If I owned this restaurant management software company, and I partner with Bank X, then how does the customer then get enough options?

Dallas Wells: Again, I think what the customers would tell you is "If you make this easy for me, there's enough value in that that I don't want to shop it around." How exclusive things are or are not can all be kind of dealt with.

I'll give you another example. This particular name has some negative press around it lately, but Uber was really kind of one of the early adopters of this kind of a partnership. Theirs is actually, I believe, with J.P. Morgan. If you think about an Uber driver who either is new to Uber, or has been on it for a while but wants a new car, or somebody who wants to buy a car and become an Uber driver, who has a better idea of whether that driver will actually succeed and be able to meet those debt payments? Uber or any random bank in town?

Jim Young: Right.

Dallas Wells: Right. So Uber knows what kinds of volumes are being generated in that city. They know what kind of income the average driver typically tends to make. If it's an existing driver, then they have even a whole lot more specific data. Not only that, but they actually sit in the middle of the payment stream. The customers pay Uber, Uber doles out the driver's share to them, they can hold back the part that needs to go to cover the car loan.

For Uber, they are helping create new drivers or drivers who can maybe upgrade and go into the more expensive services by buying a better car. So their bottleneck is finding good, qualified drivers to make sure that when people pull open the app, there's a driver nearby who will do things at a reasonable price. So they help solve their bottleneck by financing a car purchase in an easy way. If you talk to Uber drivers, there's lots of things they don't like about it. The stuff they love about it is that it all lives through their phone. This is the same way.

For J.P. Morgan, think about all the places Uber is. You're talking about thousands and thousands of car loans, again, that you can underwrite way better than by FICO and a down payment amount, which is kind of how car loans have been done forever with very high default rates. So you know more about the likelihood of that loan being repaid. You know that as that driver makes money, again, Uber sits in the middle of that payment stream, you can essentially be paid first.

Jim Young: Interesting.

Dallas Wells: So it's an easy, ready-made source of loan growth for them that, I think, will be very low default. I'm sure pretty profitable for them. Again, these are not necessarily price sensitive customers. This is convenience sensitive customers.

If you think about that same concept, that Uber knows the likelihood of success for their drivers, this restaurant company knows the likelihood of success for their customers, their entire livelihood is kind of staked on that. I think it would be interesting for banks to think about those software companies as potential partners for them. We're not talking about partners like with Lending Club where you buy some of their paper, then they can offer loans to some of your customers. I think bankers have been a little leery of that whole relationship for a lot of reasons.

I think this is a way, too, you can take advantage of some of the same big picture trends, the kind of SaaS-ification of the world. Every industry has multiple vertical SaaS companies sprouting up. Some have been around for a while and are pretty darn successful, but if an industry isn't covered by a good, strong SaaS company yet, they will be very soon. So I think there's opportunities here where you can get kind of new access to leads, to introductions, to exactly the kind of customers that you would be after, and you can underwrite them in ways that you never would've thought possible.

Jim Young: Yeah. It's really about, and I hear this kind of conversation in our hallway with developers, it's just about data sets. You get this access to really big data sets at that point.

Dallas Wells: Yeah. What our developers will tell you, what Carl, I think, has believed since he and the other founders started PrecisionLender is there's a whole lot of the tech industry that really believes that the biggest data set wins. That's why you can get so many Google services for free.

Jim Young: Because they're gathering data.

Dallas Wells: The data set is what's really valuable. They sell ads because they know more about an individual than anybody else in the world. Facebook maybe being the one exception. Same thing. Your Facebook account is free because the value is in the data. I think a lot of these SaaS companies are sitting on data that they're not really sure what to do with, and this is maybe a way for them to possibly monetize it a little bit. Again, that's something that can be worked out between the banks and the tech companies.

I think more importantly, they reduce churn among their own customer base. They're not going to go try the other platform that maybe has a cooler user interface. "Man, I got my loan through this other one. I either don't want to or can't just abandon ship on it." That has real tangible value and is a way for them to monetize that data set. In the same way, the banks get access to data that they just don't have. This data does not exist anywhere else. All of a sudden, it's just appearing. It's showing up, and there's this explosion of this kind of data everywhere that the banks would love to have access to, and here's a good way to get it.

Jim Young: I think I know the answer to this, but I'm going to ask it anyway just because it feels almost like an obligatory thing when we talk about sharing data. Are there privacy concerns at all here? If I'm the restaurant owner, and I deal with this software, is there any concern at all that now the bank is looking at data from me? We know why that's great for the bank. Is that okay for the restaurant owner?

Dallas Wells: I think for the restaurant owner, there's number one, back to the kind of pre-screened credit card idea, this happens everywhere. The question is "How deep into my business can they really see?" I think this is the important thing about it being set up properly, which is you essentially opt-in to showing your actual personal data to the bank when you click on the button. "Yeah, let's talk about a loan. That actually is something I need." Otherwise, what the bank's really asking is "Hey, anonymously, here's the criteria I'm looking for. Of your data set, are there restaurants that meet this criteria?" If there are, show them that option. Once they say "Yes," then we look at their individual case.

But otherwise, it's kind of anonymized data. Again, just like the same kind that we build our machine learning on is this anonymized data set that's really valuable as an aggregate, but we don't have to deal with the privacy issues of "Well, we're not looking at one individual customer's thing with their name and information attached to it." Same thing here. They don't have to see your individual restaurant stuff. They just have to know that you meet whatever the criteria is. Again, that SaaS company will know what a lot of those are. The bank will know what some of their own things are. Maybe it's even things of like "Hey, we want restaurants that own their own building." They can self-select for the things that matter to them, so they have some real estate collateral. Whatever that case may be. Once that criteria is met, those are the ones that get the offer. Then you can kind of decide when that real personal information gets accessed.

Jim Young: So again, from an efficiency standpoint, you're not going to be getting a whole bunch of requests for loans from struggling restaurants basically.

Dallas Wells: Right. Right. It should be ones that have kind of been pre-screened. They are somewhat kind of pre-qualified. So you know now that they meet the most important criteria to you. You know that also they have some interest because they've raised their hand. You don't have to have people guessing from the outside or, and I've seen this in banks, how full the parking lot is. "That restaurant looks busy. Let's go knock on the door." It could be busy because they're selling food at a loss. You get to look at much more qualified deals, then go through your normal underwriting process, but you have additional insights that you wouldn't have before in addition to whatever other things you want to ask for.

Jim Young: Sounds like a pretty cool concept to me.

Dallas Wells: Yeah. So what do you do from here? I think this is the kind of innovation stuff that banks have groups that are thinking about these things. I think what's important is they need to kind of widen the scope. They need to think outside of ... To your point in talking about the title of this podcast, it isn't just about fintech. Take off the blinders. There's a revolution happening in the technology world in general that's touching not just banks. We hear all about fintech because we're in banking. There's a restaurant tech revolution coming along, too. There's a home healthcare tech thing happening as well. They're all dealing with it. Some are friend, some are foes. Everybody's facing these same kind of things. So think about all of those issues that impact your customers, your potential customers, and see if maybe there's a better way to interact with them. It doesn't have to be your personal data set. Is there another data set out there that you can maybe get access to that would be a potential source of growth for you?

Jim Young: Yeah. It'll be interesting to track this and, as this whole market evolves, to see who can dive into those particular partnerships.

Dallas Wells: For sure.

Jim Young: That'll wrap it up for today's show. Thanks for listening. If you'd like to learn more, visit our resource page at explore.precisionlender.com. If you like what you've been hearing, make sure to subscribe to the feed in iTunes, SoundCloud, Google Play, or Stitcher. We love to get ratings and feedback on any of those platforms. Thanks again for listening. Until next time, this has been Jim Young and Dallas Wells, and you've been listening to The Purposeful Banker.