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AI, Relationships, and Small Business Lending
Dive into the intricacies of artificial intelligence in the small business lending space in this thought-provoking episode. At the bustling Money 2020 conference in Las Vegas, we engage with Omri Yacubovich, CEO of Llama AI, as we address the pressing concerns surrounding traditional lending processes and how AI could reshape the future. With small businesses representing over 55% of the American economy, access to tailored lending solutions becomes a crucial topic of discussion.
As we explore the tension between AI-driven personalization and the potential for privacy invasion, personal anecdotes highlight the real-world implications of data misuse in the financial sector. We unpack the challenges faced by community banks as they strive to maintain personal relationships with clients while also adopting advanced technology. This episode illuminates how AI offers a more proactive approach to lending, allowing banks to anticipate the needs of small businesses while fostering trust and transparency.
Join us to listen to expert insights on how the future of finance can strike a balance between efficiency and empathy, and what this means for lenders and borrowers alike. Don't miss this opportunity to engage with transformative ideas about the intersection of technology and personalized service. Subscribe, share, and leave a review to join the conversation!
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Welcome to the Money Pot. I'm Rachel Morrissey from Money 2020, and we're recording live at our show in Las Vegas, and so far, the day has been pretty good. I am here with my co-host, Sheryl Chen, who is the head of content for Money 2020 Asia. Sheryl has spent most of the time on the sentient stage, so I'm just going to ask you, Sheryl, what do you think?
Sheryl Chen:Do you think the future is actually human? Is the future human or is it AI? Is it AI? Is it AI? I think it will be a long while till AI can fully reign. Yeah, but for now, I think, humans, we will still be able to keep our jobs, thankfully, thankfully.
Rachel Morrissey:Very thankfully. I was thinking AI would replace me any day now. Well it can, and we are here with our guest who would know, Omri Yacubovich, CEO of Llama AI, and so how are you feeling about everything, Omri?
Omri Yacubovich:Good Glad to be here.
Rachel Morrissey:Good, so you tell me what have you seen around the show that has struck you, especially about AI, since that's your yeah, so I think it relates to your kind of previous comments.
Omri Yacubovich:I think early on people were thinking that AI will replace the blue color employees. Now they all get it. It's going to replace the white color.
Sheryl Chen:I think going to replace the white collar.
Rachel Morrissey:I think, rachel and I anybody with a data like brain dead you know what?
Sheryl Chen:I, my co-host is actually an ai co-host, so I actually joked with her that she actually stole my job. But she was so polite. She said that you know what? There are enough like. There's enough space for all three of us under the moonlight to share the stage.
Rachel Morrissey:She's the true romantic that, Aianna. Okay, we're gonna get started because we are actually talking about something besides the ai under the moonlight as they share the stage. Very romantic, she's the true romantic that, Aianna. Okay, we're going to get started because we are actually talking about something besides AI, but it is related. Sheryl, do you want to go ahead?
Sheryl Chen:Yeah so maybe as a first question, as an introductory question, can you tell us the mission of what Lama AI does?
Omri Yacubovich:Absolutely, so we started the company about three years ago. Actually, here does Absolutely. We started the company about three years ago, actually here at Money2020.
Sheryl Chen:Nice Money2020, baby.
Omri Yacubovich:About two weeks before Money2020 2021, we kind of hit the nail on the problem to our after, and that's what today I call the small business lending paradox, meaning everybody talks about lending to small businesses, everybody wants to lend to them, but only a few banks can actually achieve that. So we bought flight tickets, came over, met with about 20 bankers in the course of 48 hours. It's not like you didn't organize these networking events like you're doing in this show, so it was much harder Cold calling, emails, whatever you want but we did secure these 20 meetings. And what we learned? That not only that the problem is real, but this is something that bankers are looking to solve, because small businesses are kind of the backbone of our economy. They represent over 55%, I think, of businesses employing probably around 90% of the employees across the states. Wow, I think of businesses employing probably around 90% of the employees across the states.
Omri Yacubovich:Our mission is to help and bridge the gap in small business lending, helping small business owners get access to bank-rated financials and basically what we call fur capital. It doesn't need to be only from banks. We also have some good partners that are non-banks. The idea behind it is to try and avoid and I hope I don't step on any toes in here but to avoid the 1,000% APR on some merchant cash advance solutions.
Rachel Morrissey:Well, this is really interesting because we were going to be talking about personalization, and I think most of the time when we think about personalization, or when people talk about it, it's about a singular consumer, like the lone customer, right? I remember years ago people were talking to me and were like can't you wait for the day where you have to? You know you're flying into the new city and at the hotel they've already figured out your likes and dislikes and the tickets to the ballgame are waiting on the counter for you. And there was a part of me that was like yeah, that sounds great. And there was a part of me that sounds like no super creepy.
Rachel Morrissey:I have no idea why a general hotel would know what tickets to a ball game I want to get.
Omri Yacubovich:And guess what Today? They do know.
Rachel Morrissey:They do know, I know. But then when you're talking about it from the perspective of what La Maillard is doing, sure, there's that part of it, but how does this apply to small businesses?
Omri Yacubovich:That's a great question. So first, I think that in the financial industry personalization is even more scary than in the hospitality industry, because the thing they can know about you, if it's kind of misused, could be disastrous. And I think there is a famous story, I think it's about Walmart.
Sheryl Chen:Yes, Walmart or Target. The 16-year-old yes, do you know this story. She knew that she was pregnant even before her father knew that she was pregnant. Yeah.
Omri Yacubovich:For her parents. I think she was 16 years old or something.
Rachel Morrissey:She was. She was 16. It was Target and it was a long time ago, even from now, a long time ago, 10 years Because I was in grad school at the time and she had gotten information to help her buy things that would aid her pregnancy. For when the baby came and her parents were like what in the Lord's name is going on? And then she was like, oh, I think that might be for me. What a way to tell it is, it is, it is.
Sheryl Chen:It's so crazy because I was just telling Rachel yesterday that the day before I was telling a colleague about LGBTQ issues and then the very next day I was telling my counterpart, ian Horn, about going to Phuket and just going to a villa doing nothing and just chilling after the Asia show, and the very evening I received an ad from Agoda telling me to go to a gay villa in Phuket. Did Agoda just out me?
Omri Yacubovich:Or your boyfriend? I'm not sure. Somebody somewhere is asking those questions.
Sheryl Chen:Yeah, so to personalization in financial industry.
Omri Yacubovich:Sure. So personalization is another tool to solve problems, right, in my previous background, I co-founded a company in the e-com personalization space, so we didn't do anything like Target intentionally, but we did help figure out, kind of, if you're entering an e-commerce site and like pink shirts or jackets, why should you get a black jacket as an offer? So product recommendation was actually there to solve a real problem, which is kind of the confusion among all the options that you see in the store and I can give you tens of other examples not related to FinTech, hence I'll stop but the idea that personalization is another tool to solve for a real problem again in the e-com world, it's low conversion rates and the inability of people to find what they're looking for. When we're thinking about AI in the fintech world or in the lending world, there are a few things that it can do. One of them is personalization in a way that it helps the borrower get to the finish line with kind of minimum intervention or minimum iterations with the RM. Now, with that being said, I think that community banks pride their relationship with their clients, so they're not looking to be replaced by an AI chatbot or AI agent, because then they lose the relationship. And that's not even the big bottleneck in small business underwriting. Yet the ability to personalize the experience helps the RMs do a better job. So they don't need to draft now tens of emails a day saying hey, mr X, you forgot to fill in your tax returns, can you please do that? The system can generate it automatically on their behalf. But then all they do is a click of a button and that email is sent out. So they keep full control as they like. But they don't need to do all the writing in order to make a personalized email based on the context of the client, based on the step that they're in and also any nuances that are also related to regulation, as if you need to unfortunately decline opportunity, you have to send an adverse action notice and guess what? That that one should also be personalized, meaning providing the reasons why do you decline it. So again, it could all be done manually, and that's how it has been done for years, but the ability to personalize the message and use Gen AI to generate those responses are a crucial part on the personalization side.
Omri Yacubovich:Another example of personalization and that's kind of the more advanced banks, if you think about the loan journey, you typically start by choosing the product that you need meaning SBA, loan, auto loan, whatever that is and then it will take you forward with a a closed set of questions and documents that you need to address In our world. You should first say who you are. If it's a business, what's your business name, what's your address, how much money you need and what do you need it for and then the system can automatically recommend what's the perfect product for you. So instead of getting declined on an SBA because of eligibility criteria that I don't know, they do minimum 100,000, you need only 90,000. That's a stupid reason to be declined, but guess what People are being declined for that today? The system can automatically say, hey, this is the right product for $90,000 for working capital. So that's just another flavor of the ability to personalize based on data, both declared one and then data enrichment for third-party sources, governmental databases, open web, et cetera.
Sheryl Chen:So the thing with AI, as with everything else, is that we need to draw a very fine line right, a fine balance. So how can financial institutions draw a line between creepy and being helpful, like maybe oh, I heard that you're planning to propose to your girlfriend soon. Like through the iPhone, I've been listening to all your conversations. You're planning to propose to her. So here's a home loan, because I think you guys are going to be moving in soon.
Omri Yacubovich:So I think there is data usage and data abuse. You don't want to abuse the data.
Rachel Morrissey:Yeah.
Omri Yacubovich:That means that you shouldn't collect everything that you can collect. So if the bank collects only the data that they need in order to assess the risk for a certain business or a certain borrower, that won't be misused in the fine line you're talking about, but it will be used to make sure that it's a good borrower and, furthermore, I think the more data that they have over time, the wider range of borrower they can serve and basically serve more underserved communities that, if you just tie your models to FICO score, as a lot of them do on the consumer side, you're limiting your ability to lend to potentially good borrowers.
Rachel Morrissey:Right, especially with some of these less served communities.
Omri Yacubovich:Underserved.
Sheryl Chen:Underserved communities.
Rachel Morrissey:When I'm thinking a little bit about this idea of small business personalization, what do you think that small businesses would look to to the banks? What are they expecting when they say, when you say a personal experience for small business, because the personal experience for you or me is not necessarily exactly the same thing as a personal experience for a small business that you or I would run right. So what would a small business think of as a personalized I mean loan?
Rachel Morrissey:you know, being told nicely and legally that you didn't qualify or you did qualify, or that you might qualify for something that was smaller or whatever, is one thing, but what about some of the others Like are they looking for stabilization? Others Like are they looking for stabilization, are they looking for more information about cash flows and treasury management? What is the kind of personalization that you're really talking about for that?
Omri Yacubovich:So, first, behind any small business, you have you and I standing behind it. That's where they're running the show and the ones that are applying. So the personalization is kind of tuned to how we feel about it and our one that are applying. So the personalization is kind of tuned to how we feel about it and our experience in the journey. That being said, the ability to personalize the offering is tied to the data that bank has.
Omri Yacubovich:So, instead of waiting for someone to come and say, hey, I needed cash yesterday which is a scenario that banks actually would not like to give you that cash necessarily being proactive about it and saying that this business maybe the hospitality business that you discussed they have some cycles.
Omri Yacubovich:So, before the next cycle, saying, hey, it seems like a great business, you're probably going to hit the low season soon. You need some cash to bridge cash flow issues. So that type of personalization in a way allows the banks to be more proactive and kind of more helpful for their clients. Furthermore, you see some tools that embedding tax returns into the ecosystem, right. So basically, it provides more tools to the business owners to run their business better. Back to the more simplistic way of thinking about it business owners are busy running their business during daytime and whenever they're free to deal with their financing, their bankers are probably already asleep. Typically, they live on different time zones, now how do you bridge that? Because I think every bank wants to be useful and be accessible to their clients, and having the ways to do it in parallel, asynchronously and, even without an RM, provide some information or help the owner get through the finish line, that's another huge value that they can get.
Rachel Morrissey:So it's a way for them to actually personalize it to the time of the actual owner's need, as opposed to worrying about traditional banker's hours.
Omri Yacubovich:Call you. 9 am your first meeting.
Rachel Morrissey:The call center that's like, we're open from 9 am to 5 pm on. Midwest time. Yeah, I can see that that would be very interesting.
Omri Yacubovich:And you're touching on another important point, those automated systems that are sending emails and texts. They typically have kind of a rule base. Like you said, 9 am to 5 pm. Having the ability to understand when someone is opening their emails or when do they engage with their platform, when do they click the clicks, allows the system to become smarter and know when to try and engage. So, whenever they're back at home Now we're not tracking their geography, but the system can track the time of the day that they're interactive, so the system can better approach them during these hours and say hey, you forgot to fill out your tax returns. This is how you do that forgot to fill out your tax returns.
Rachel Morrissey:This is how you do that. What do you think about something like an AI almost being, or the banks using this information to personalize? But, for example, you said that there's businesses that are cyclical. They can be cyclical yearly, they can be cyclically quarterly, but they know that they're talking to their client when times are in the fat, they're good. And what do you think about a bank that says, hey, you're not always going to be in this spot, this is a good time to put away. This is like what is the, what would be the kind of limits around that, so that you are not kind of overextending yourself there?
Omri Yacubovich:I think that's conflict of interest. Question right.
Rachel Morrissey:It does feel because we were talking about Amazon. Right, that was part of the introductory to the, to the in the inside the app for this, and it pretty. I mean, yes, what Amazon does with data is quite amazing, but it's pretty easy, like she said, to have some input about. You know, I'm interested in this and I'm interested in this and they put two and two together and they put that you know shiny jewel in front of you and then you're like you know, I'm going to click and impulse buy, but that's the mission of a. Does that fit the mission of a bank? Not at all, right. So how does the personalization fit the mission of a bank?
Omri Yacubovich:So I think the limit that some bankers see in terms of personalization they think about the relationship managers that are interacting with clients and that's what they interpret as relationship or personalized relationship. My claim is that that's not a personalization. It could be a person delivering the message but using the data like you talked about seasonality and other stuff to have the rm call you at a timely manner saying, hey, I, I see you, I understand your business, this is what you need and this is why you need it is like a thousand times better than just calling you out of nowhere saying, hey, we have a new loan to offer you. It's like oh, my gosh yeah.
Rachel Morrissey:And why you would need it at any time. It has nothing to do with the product design.
Omri Yacubovich:The compelling event is something that differs from one client to another, especially in business. It has a lot of data points that could indicate that that could be someone's looking to expand their business or just bridge any cash flow issues, or maybe the entire industry is on its way down. Think about COVID and restaurants. That's a very simple example. But what if banks could reach ahead of time and say hey guys, you need to cut off your costs. That's a trajectory, not necessarily that a single business owner can see the future that far, but I think that's a great tool for bankers to really be trusted advisors and not just salespeople.
Sheryl Chen:Yeah, so this is also circling back to data usage and what do we call it? Misusage.
Omri Yacubovich:No, no Data usage and this is abuse Abuse. We coined a new term Correct Abuse Abuse yes.
Sheryl Chen:So I also wanted to, when we talk about data usage abuse and also, like we also want to like take a peek on what people have been they have been sweeping under the rug, right so, when it comes to working with financial institutions, banks what are the actual reasons for data silos and lack of personalization that's happening right now?
Omri Yacubovich:I do think that they started personalizing things. So the data silos exist because it needs to exist, because of regulatory, of course. Even if you think about using Gen AI in the context of lending, it has to be siloed. You don't want one client's data to leak to another client, so we're looking at it always in the scope of specific application or applicant data silo that allows to create those insights, not just for communication purposes or for promotions, but also to actually assess the risk and help the underwriters. And that's where the big value is helping the underwriting team to be more efficient, smart about it and really understand the business.
Omri Yacubovich:Because when it comes to business lending and I think not a lot of people are aware of that that's not as easy as underwriting a consumer loan, because for a consumer, you take their FICA score and a few more data points and that's it. And it's not as lucrative as underwriting $100 million deals that you do whatever you do and then you give them a check at whatever rate and hope for the better doors of more established businesses. The small business sector is built out of thousands of different business types, so think about makes codes. You've got I don't know how many, but thousands of them right, and that reflects different business characteristics. Now, if you're an underwriter at a bank, nobody can expect you to be an expert at 20,000 different industries, and I think that's another kind of implication for, yeah, a way to use AI that allows you to basically teach you and make you more knowledgeable about industry's pitfall or benchmarking or any characteristics that otherwise have no way to assess.
Rachel Morrissey:Yeah, it'd be a great way to get extra insight into any industry where the banker is supposed to. You know, the ideal is, of course, the banker is an advisor and can really help anybody and understand the industry. But nobody can be an expert about every kind of small business or every kind of industry. So this idea of this kind of data insight helping feed and teach the underwriters and make them become experts in more kinds of businesses is kind of fascinating. If you think about it. It really changes that because it would eliminate or it could not necessarily, but could eliminate a lot of biases. Based on my experience with one industry and what I would think of that, it might have very little to do with the realities of another industry and create new biases, though.
Omri Yacubovich:Create new biases.
Rachel Morrissey:So there we go. That leads to the next question. So talk to us about that. How does it create new biases?
Omri Yacubovich:So, before creating new biases, I think it's not about educating the underwriters but putting the spotlight on anything they should be aware of before they approve or decline kind of opportunities, because it's endless Extending their knowledge.
Rachel Morrissey:I'm not trying to indicate that they're not doing their job.
Omri Yacubovich:When it comes to biases, I guess, yes, people are biased, so if they had bad experience with a loan that went south in a certain industry, they're probably going to look at it in a certain angle that is less favorable. So when you automate some of these decisions or recommendations, you definitely can get rid of these biases. And yet I think from the regulator perspective, you still want underwriters to sign the approval and say you can do it, or at least the parameters that influence the decision. Even if it's fully automated, the new biases could be the data sets that the AI was trained on. So if it's trained on a certain data set, that could create some biases, and obviously there are ways to avoid that.
Rachel Morrissey:There's ways you should avoid that, but it's an interesting problem solution that leads to another problem that needs a solution.
Omri Yacubovich:That's why I think that AI will not take our jobs.
Rachel Morrissey:That's why.
Omri Yacubovich:For now? For now, I think people don't like the equation of the industrial revolution to the AI revolution, but I think there are some similarities and overall we need to be optimistic and I believe we might have more free time. That's a great thing.
Rachel Morrissey:I remember when I was studying economics, they've talked about Keynesian theories, is it?
Rachel Morrissey:Invisible Hand no that's Adam Smith, but in Keynesian theories, part of his thing was that capitalism was going to be so efficient that we would all have a lot more time on our hands. We'd only work like a 15 hour week and then all of a sudden, because the production would be too high, and then we would only have to work a 15 hour week and we'd have a lot more leisure time to educate ourselves or read or do things that we love, and we wouldn't need to work so many hours. I'm not giving him a star for that. I think he underestimated certain things when he came up with that, but I still think that there's a little bit of an ideal there that we could reach for, which is, if we are going to have tools like this, maybe we should be thinking about how we really want to apply it to productivity and what that will actually mean for human beings.
Omri Yacubovich:But I think that part of capitalism people are trying to get the most out of everything.
Rachel Morrissey:That's why I thought it was a kind of an overestimation.
Omri Yacubovich:But even in today's world, if it can be more efficient, and I can tell you that this startup, lama, is way more efficient than my previous company. Not because people are working hard. They are working hard, but they have way more tools to achieve.
Sheryl Chen:They're working a lot smarter.
Omri Yacubovich:Exactly hard, but they have way more tools to achieve. They're working a lot smarter Exactly, but they're working as hard but smarter, so they can produce way more. So, in a capitalist world, we'll just try to get more. So I don't think we'll free more time.
Rachel Morrissey:I don't think we're going to end up with a 15-hour work.
Sheryl Chen:Yeah, you're going to spend all the other time coming up with like 15 other side hustles.
Rachel Morrissey:I spent all the other time coming up with like 15 other side hustles. That's probably true. Okay, well, we are at time. That was really fast, is there anything? You want to tell us before we go.
Omri Yacubovich:Thank you again for having me.
Rachel Morrissey:Thank you so much for joining us.
Omri Yacubovich:It's a great show.
Rachel Morrissey:Oh, thank you. Yeah, I hope you so much it's a great show. Oh, thank you. Yeah, I hope you all enjoying your time, okay, so, uh, thank you everybody. Thank you, Sheryl, for being my co-host for having me.
Sheryl Chen:I wish we had more time. I wish we did too and thank you.
Rachel Morrissey:Uh, we want to thank our live audience. We want to thank our podcast audience. We want to thank our podcast audience. If you guys think you have a great idea for a podcast episode for the Money Pot, please go ahead and email us podcast at money2020.com, and we would love to hear from you. And to all of our listeners, go ahead and tell everyone to subscribe. Have a great day.
