In this week’s episode, Suresh talked all-things-FinTech with Greg Palmer: columnist, podcaster, and Vice President of the Finovate Group. In the first half of what turned out to be a fascinating overview of some of the latest trends and innovations in the FinTech industry, Greg spoke about how prioritizing customer preferences has been front and center of almost every new FinTech venture that he has seen. In addition to that, he believes that one of the key points where FinTechs are starting to diverge from more traditional financial services companies is social responsibility: they are addressing challenges in the financial system from both a business standpoint and a social standpoint.
In the latter half of the discussion, Greg dove deeper into a few specific trends that we see in today’s FinTech landscape. He touched on how peer-to-peer payment providers need to differentiate themselves to gain “functional loyalty” from consumers, the high cost of storing data, the need for credit-scoring to undergo a massive transformation, and the use of AI to measure ESG standards. Last but not least, Greg predicts that AI will underpin nearly every organization’s process – FinTech or not – over the next few years.
About Slaves to the Algo
Whether we know it or not, like it or not, our lives have been taken over by algorithms. Join two-time entrepreneur and AI evangelist Suresh Shankar, as he talks to leading experts in various fields to understand how they are using or being used by algorithms in their personal and professional lives. Each episode highlights how businesses can leverage the power of data in their strategy to stay relevant in this new age of AI. Slaves to the Algo is brought to you by Crayon Data, a Singapore-based AI and big-data startup.
Suresh Shankar is the founder and CEO of Crayon Data, a leading AI and big data start-up based in Singapore. Crayon Data’s flagship platform, maya.ai, is the AI platform powering the age of relevance.
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Full Transcript of S2EP7:
Suresh:
Hello viewers and listeners. I’m Suresh Shankar, Co-Founder, and CEO of Crayon Data, an AI and Big Data startup headquartered in Singapore. Welcome to this episode of Slaves to the Algo. That’s right. Slaves to the Algo: my attempt to demystify the age of the algorithm which seems to be taking over our lives, both professionally and personally.
In this episode, I’m delighted to have Greg Palmer, a FinTech expert, a columnist, a podcaster, Vice President of the Finovate Group which as we all know is that real connector between traditional banking, consumers, FinTech companies, and director of FinTech strategy at the Informa Group.
Finovate actually does a lot of showcasing of cutting-edge banking and financial technology algorithmic and otherwise through a unique blend of what they call the seven-minute demo and key insights from thought leaders. Welcome to the show, Greg.
Greg:
Yeah, thank you so much. My pleasure. I really appreciate you having me on.
Suresh:
And, Greg, you’re a podcaster yourself and so I think what I hope to do is to have a very interesting conversation with you about things that you are seeing about how data and algorithms are being used by FinTech’s, by banks, you have a fairly global perspective, and you sit in the hotbed of technology in Seattle.
So, what I like to actually begin the show by asking my guests a slightly more personal question, we’re all affected as individuals, you know, we all love technology and use technologies in some form or fashion, but we’re also affected as individuals with the development of data and AI and what it’s doing. And so, one of the things I like to ask my guests is can you share some examples of some really nice ways in which great algorithms or a data set that has either impacted your life either positively or use something in a fearful way?
Greg:
Yeah, absolutely. So, you know, the first thing that comes to mind is looking at our Finovate conferences, that’s really the first time that we kind of played with AI technology ourselves on a professional level and this was really interesting for us as we started to see what was possible around intelligent matchmaking and bringing people together you know creating these connections between two individuals.
So, you know, from a professional standpoint, I think that’s really been the artificial intelligence that I’ve seen, that I’ve played with, and it’s really worked wonders for us and I know our attendees enjoy it as well because it lets them kind of get to these better meetings faster. They can kind of sift through a lot of things and connect with the people that they really want to connect with. On a personal level, kind of outside of that professional setting, I think that you know the AI, that I really enjoy the most, and as a user is the AI that I don’t even really see right? When I start to see something that I feel looks like AI, it can be a little bit off-putting right? It can be something where you start to say, wait, how did you get that information or how did you make that connection.
It’s the ones that you don’t see that happening where you get these excellent user experiences, whether it’s as simple as you know, getting a song recommended to you. You know hey you enjoyed listening to this artist, maybe you would also like this other artist, you know, things like that I think can be really fun or whether it’s that, you know, I always kind of bring it back to financial institutions. When your bank can anticipate a need that you have when they sort of say we’re guessing that you might be thinking about this and so, you know, here’s an offering that’s targeted, that’s timely, those types of situations I think it can work really well.
Where it can be more off-putting is if you feel like you’re being sold to, right? If you feel like there’s somebody who has, you know, they’re kind of eyeing you up and like well we know all of these things about you and we know that you’re probably about to go to Home Depot tomorrow and buy X amount of tools because we can see that you’ve just made this other purchase over here, and that’s where it can start to feel a little bit creepy.
And so, I think that’s really the balance, right? These, when it can offer this seamless experience when it can offer something that you know presents a choice to you or gives you something that says hey, we think you might enjoy this, then it can be really helpful you know? That soft touch is key. When it’s more overbearing when it’s something that is a little bit more forceful, or a little bit more unexpected and maybe not as good right, maybe the recommendation is not quite in line with what you actually want to do, that’s where it can start to be a little bit problematic, and that’s where you can leave that bad taste in your mouth.
Suresh:
And that is such a fascinating summary of all the opportunity and the wonderful potential of AI and the challenges right when it’s seamless when it’s serendipitous, it’s wonderful. And when it’s stalking you or selling to you it can be ughhh.
I want to go back to what you just said about the intelligent matchmaking meetings. That itself sounds like a billion-dollar idea because which person in the world or listener to this podcast, wouldn’t want intelligent meetings with actually people that you value. Could you tell us a little bit more about how you do that?
Greg:
Yeah, yeah absolutely. So, I mean, from, from our standpoint it’s fairly straightforward you know, as a user you would go in, you create a profile, you list out you know this is who I am, this is what my background is, and then you create a series of tags, about yourself. You know this is how I want to tag myself and then you get on the next page you get kind of a, you know, here’s who I’d like to meet the type of page and so you can start to pick who you’re interested in talking to, you know to people about this subject matter. We actually go a level deeper than that it’s not just what subject matter but it’s sort of which side of the conversation, are you on, are you looking, are you a FinTech who’s looking to connect with bankers? Are you a banker looking to connect with FinTechs? Are you a venture capitalist who’s looking to connect with anybody working on this, in this space? Are you an analyst or somebody else in the industry looking for that hot scoop?
And so are you just kind of looking for, you know the very specific FinTech boundaries. There’s a whole bunch of different ways that you can sort things and personalize them, and then the system on the back end, just you know, starts to create meetings for you. You set up you know I’ve got two hours or however long you want to spend it can kind of plug-in time for you. And then, you know, it’s as simple from an attendee standpoint of just showing up. So, you know when we were doing events live…
Suresh:
You know I’m a guy who’s out there trying to sell something and I look at this I have my two hours I filled up my tags I said who I want to speak to. And basically, the system says to meet this guy, meet this guy, whatever it is, and gives you the location inside your conference. I mean, yes, I wish we were back at physical conferences, but that day will come. And similarly, if I’m a banker, I actually see my schedule and it’s all out there populated just turn up, have your chat and go on, is that it?
Greg:
Yeah, yeah basically. So, the live event experience, which we’ll be getting back to at Finovate Fall this September, we will be able to bring at least some people back in, you know, we’re still working with the city and everything, City of New York and the local governments there to figure out how big of an event we can actually do.
But yeah, how it works, you know you would just get a notification okay your 4:15 is waiting to go to table 20 in the networking space and so you would go there and have that meeting and then you know at the end of it, and you can decide, do I want 15 minutes, do I just want to have your 10 minutes there’s a lot of customization that you can, in ways we can set it up. We’ve kind of standardized on 15-minute meetings that seem to be really effective.
But we’re actually trying to format now with three-minute meetings where you just get a bunch of rapid-fire three-minute meetings really quickly and, you know, so, the onus is you have to come to those conversations prepared, you have to be ready to talk about what you want to talk about, but you’re in three minutes, you know, generally, if you want to follow up and have a deeper conversation with somebody. So, you know we’re kind of playing around with a lot of different time increments. Really the end goal is all just about making that connection, letting people meet the right types of people. And of course, just like anything else, it’s an imperfect tool. You know they’re going to be times when somebody…
Suresh:
And do you follow through on that subject? Does the AI or the data actually come back and say okay we set up these meetings for you? Do you ask people which ones of them were useful, and you have some learning that says okay, you know, these kinds of things work better than other things and, you know, in which meetings turn out to lead somewhere?
Greg:
Well, the data that we track is more around which subject matters are most appealing, you know, see which groups, people, which groups are most selected, which types of technologies are most selected, and as you can imagine that’s really valuable information for us because it helps us keep our finger on the pulse of the industry. What are people really interested in talking about? What are they interested in connecting about? So that type of data that we get is really helpful as we plan future programs .as we plan networking spaces, and of course, we’re continuously updating the subject matters that we have that are available for you to meet with other people about. So that’s really where we get the most useful data.
We are of course interested in the raw numbers you know what types, how many attendees actually, or how many of the meetings actually happened. And what we found is that the meetings that are scheduled through this platform, tend to be really likely for people to follow through and connect with them, and I think it’s because they’ve kind of gone out and said you know this is specifically what I’m trying to do. You know it’s a lot easier to get meetings to happen when both parties are really invested, they both got something committed to the idea. So that’s, that’s where we’ve seen it be really effective for ourselves.
Suresh:
And I’m going to come back to this a little bit later. But I think it’s fascinating because I think one of the biggest problems that people have in the world is too many meetings. Too many meetings that don’t lead anywhere. And Finovate has actually built something to better match the meeting process. I think you guys are sitting on a unicorn idea of your own. You should spin this off as a separate company. But we’ll come back to that.
Getting to your core area of what Finovate does and what you’ve been doing for many years now, which is in the banking industry. And you recently, Greg, wrote an article on FinTech Futures, about your seven-year-old opening a banking account which is fascinating right? Because this is what bankers have celebrated about: can I get into the baby’s born, can we open a bank account? And your son told us a lot about what we should know about banking from, you know from your article. And could you tell us, for example, today, what are the trends that you’re seeing? About, you know what people are looking for? Because this whole idea of a relationship between the bank and the consumer seems to be changing, because it’s no longer a bank, sometimes that you’re dealing with. And you know what you think are the things that people looking for in this whole relationship between banking, which is very necessary, banks may not be, and consumers.
Greg:
Well, I think there’s a lot to unpack there. And I think the first thing that really struck me, so, first off for anybody who’s wondering, I didn’t pressure my kid to get a bank account in any way shape, or form. This is one of the things that we’ve been living together, he’s been going to school right next to where I’ve been working for the past year, which I’m sure is true for a lot of you out there listening, and so obviously clearly rubbed off on him. And he came and said I really want a, I want my own bank account what he really wanted was, you know, a physical card, he wanted to have his own debit card, but also, he wanted to feel like he was a part of, you know the world that I, that I work in and live in. So, from that standpoint, I think it was really good.
So, when I, when I took him, you know I was really curious because here’s somebody who’s completely new, completely green to the banking system. And so, I wanted to make sure I captured his thoughts because this is a unique opportunity for somebody. Their very first experience. And what was really surprising was a lot of what he was saying, are things that we as an industry kind of already know, you know, we understand the importance of the priorities for Graham. He wanted to have, personalization, he wanted to be able to choose the exact card that he had, he was really pumped about being able to do that he wanted something that he felt was unique and personal to himself. He really, the idea and we kind of set this up, and I didn’t invent this, but you know the kind of three bucket children’s banking system of, you know, spend, save, share.
He really was fascinated by the share side of it, you know. I think he’s been you know, reasonable saver he’s seven, so you know he’s not like super disciplined with this money, but, but when I told him…
Suresh:
Cookies?
Greg:
Hahaha right yeah, it’s popsicles, it’s the freezer aisle at the grocery store that if you can make it through that without spending money that’s always a that’s a good day. But, but I was telling him you know you can take some of your money and you can set it aside to donate to something that you’re really passionate about and he really enjoys red pandas. We have some red pandas at the Seattle Zoo. He loves them, and when he kind of made this connection like I could donate money to, you know, the World Wildlife Federation and actually help keep animals in their habitat, it really resonated with him and again this is something that we know right? We, there are so many studies out there so much research that says that you know the younger generations, in particular, want to feel like their money is doing something good in the world.
They want to feel like that, you know they’re a part of something bigger than themselves and they’re able to have their money, create a positive impact somewhere else. And so, for him to be able to do that was really exciting. And again this is not something new, but this just kind of emphasizes this point, you know, if you look at where we talk about what customers want: high level of personalization is key, high level of social impact, being aware of that is really key. The other one which I thought was really interesting was I asked him, you know, what do you anticipate your, why do you think it’s easier to pay with a card than with cash? And he said, I can’t make a mistake, you know I don’t have to worry about giving the cashier the right amount of cash. You know for you and me, this is not really a big concern at that level, you know you can pull a 20 out of your pocket and be confident, but for him, at seven years old this is actually something that he’s thinking about you know he doesn’t want to do something that’s potentially embarrassing in front of somebody else.
If you extrapolate from that and look at it, you know people want their banks to offer them some kind of safety net to protect against the ability of them making a mistake, whether it’s an embarrassing mistake or whether it’s something that’s more sinister. You want to have this feeling that there’s a safeguard there’s a rail in place, that’s going to keep you from doing something that that you really don’t want to do. And so, you’ll look at that as well and you think, again, that particular example, maybe not as relevant once, once people get older, but you know how many people struggle with what the financial industry considers to be kind of basic financial health? Whether it’s saving, you know, budgeting appropriately, people have difficulty in this area managing their finances and a lot of them simply have never been taught. You don’t know the best practices.
But there’s real value for a financial institution who’s able to anticipate those potential problem areas and say, you know, we can help you avoid making that mistake we can make sure you’re set up. So, you know, those are just three of the ones that that came out of that conversation, and again, none of that’s brand new, but it was really interesting to have those reinforced by somebody who hadn’t heard about any of them and was coming into it with a completely clean slate.
Suresh:
Well, Greg, I think what is fascinating for me as you’re telling the story is that your son seems to know something, he seems to be reading Harvard Business Review because two of the five new Ps of marketing are personalization and purpose. And I think you know consumers want that and I think your sons are displaying at an early age and I think all brands and all banks, and everybody needs to wake up that this is what consumers want to do.
But coming back to I think how technology can enable these things, you know, we talked about the personalization aspect we talked about the purpose. Now do you see, and I think you deal with a fascinating thing because you’re in between. You talk to banks, and you talk to FinTechs. Now, which of these people, which of these two industries has more grasped the problem and I would say the opportunity that technology is providing to change some of this stuff? And can you share some examples of what you think, you know, you know are fascinating ways in which people are using data algorithms, technology to solve, personalization, or the purpose problem if you will?
Greg:
Yeah so, I think it’s you know is I’m going to try and avoid painting with too broad of a brush here because, certainly when you look at your banks as an entity, in and of itself, your banks and bankers are so many different kinds of financial institutions and there are people within, in roles within banks, you know, whether they’re major multinational banks or smaller community banks anywhere in between, who I think really understand the value of these pieces.
But you know I think it’s pretty clear that the FinTech side of the equation is spending more time looking at you know, especially personalization, right? And more so the ability to how you go about doing that I think is something. And also, I think the types of people who tend to be attracted to the FinTech space, you know you largely do that because you see a hole somewhere, you see an opportunity somewhere, and so that that can make you want to get engaged.
But we hear a lot of FinTech companies, who really look at the customer as the first and foremost, piece of the puzzle you know I was talking to you played or the CEO of Backbase and they’ve been a fun story for us we sort of watched them grow. I remember that being in my first Finovate back in 2010 and to where they are now is it’s incredible what a journey that they’ve been on and we’re really happy to have been part of their story. But, but, you know, in my interview with him, he said that the customer for them is their North Star. That’s the thing that they always think of. Now what they do is they build products which are very attractive to banks, they’re easy to use by banks, but by elevating that customer to that top piece, it makes it a lot easier for them to make these crucial decisions when, when they come up, and it gives them again that guiding light. So, I think and they’re certainly not alone in that there’s a number of other companies that we see who are doing that very well.
When you get to the kind of more social responsibility side of things, here’s where I think you see FinTech’s really starting to pull away, from some of the banks that we have. I think a lot of people look at the financial system that we have, and look at, you know, the way that we give out credit, the way that we, you know, help people manage their money, move money overseas, all of these pieces and look at the inequalities that exist there. And I think you know from a FinTech standpoint there are companies who’ve seen this massive opportunity from a business standpoint and massive problem from a social standpoint. And I think they’ve done a lot more of trying to really push and fight for that. Now the good news is, there are a lot of banks who are now starting to really hear that message and starting to push forward so I think over the next couple of years, you’re going to see a little bit of a split in the banking industry between companies who really have heard that message who understand that message and companies who maybe haven’t as much.
But, you know, the banks that allow people to, you know, tap into this kind of social responsibility angle, I think, are the ones that are going to be in a really good position because we know that you know the younger generation you know that this under 30 group, even under 40 maybe depending on where you want to draw your generational lines. There is a significant motivator for them in terms of who they want to do business with, where they want their money to be, what they want their money to be doing when they’re not using it. And so, I think that, again, there are people doing really strong work on both sides. In my experience, a lot of these issues are being driven by FinTech innovators who are kind of pushing things forward. And a lot of banks really kind of need that pushes they need the industry to move in some sort of, force them to catch up, or else they risk kind of falling behind everybody else.
Suresh:
You mentioned several fascinating things, Greg. One of the things you talked about is this whole area of payments and how people are trying to do more payments and more, whether it’s cross border or even within, you know, within between businesses and companies and so on. And this is obviously a massive area of both technological explosions. I mean you know on the one hand you have the consumer place like Klarna who is saying, you know, they built the buy now pay later revolution. You had Stripe say I’m building a new backbone, you have Zelle, you have Venmo.
And now you have WhatsApp and Signal, even Signal is trying to get into this whole area of payment, right? I’m not asking you to pick the winner, but what’s your take on the whole area about because most of these depend on two things. One is that they depend upon the convenience of like you know how easy they make it to pay but they also depend upon actually understanding the consumer enough to say, this is exactly what you want and let me give that to you.
Could you share some light or shed some light on what you think are fascinating uses of technology that you’re seeing in this space?
Greg:
Yeah, absolutely. So, I think, you know, the first thing is from a user standpoint, I think users are to some extent provider agnostic when it comes to, which I don’t think they have a lot of brand loyalty in terms of how they want to move money. They have functionality loyalty, they want it to do what it should do they want it to do it quickly and well, beyond that, you know, I don’t think they really care too much. You know, and most of the people that I’ve talked to kind of outside of my professional life. They’ll use Venmo when it’s easiest they’ll use Zelle when it’s easiest, and I think there’s an opportunity for other brands to get involved in that as well.
But I think ultimately what it’s going to come down to are, there’s institutional advantages that you can get when you’re Zelle and you can, you’re automatically inside the gate of a lot of financial institutions. That right there reduces a lot of friction, and that makes it really compelling for customers to use it because it’s simply the easiest option, you know? There’s the least friction option. Venmo is another low friction auction, it’s very easy to use it. The fees are pretty reasonable from a consumer standpoint. And so, you know, again, a lot of people have gravitated towards it.
I think when you look at the future of that space, it’s really difficult to pick who the winner is going to be because what I expect to happen is similar to what we saw with a kind of social media network. There are going to be a lot of competing products that look very similar and so you know what’s, what’s the difference between a Facebook and a MySpace, right? How does one of these into becoming gargantuan? Jeez, that was tough to say. And one of them becomes a punch line for late-night hosts. And so, I think, I think that’s really where we’re at right now I think and what, what difference it is it comes down to, you know, the number of people who start to use it, you know, just the sheer snowball effect of the more people that use it, the easier it is the more frequent it is so the more you need to have it too.
And then the other side of it is, it comes down to, you know how these brands position themselves, how they market themselves, how they’re able to, you know, generate that excitement and that enthusiasm to really resonate with people. And so, you know, you look at it, there’s a variety of ways that you can do this. You can look at the success of Ali pay, and you think well, you mean that’s difficult to replicate in a situation where you can’t say hey, you’re all using this now. That’s a pretty good advantage to have when you’re trying to grow users quickly.
But you look outside of that and you think what’s looking at, you know, how does Venmo defend their position at this point? How do banks who look at Venmo and say how come all we need to fight back against this is too many people holding money inside Venmo? They should be holding that money in our accounts, how do we go back and try and fight for some of that share and get some of that back? And you know the way that they can do it is, make it really easy, make it really smooth, and, and then just mark it like crazy, because I think it really does come down to creating that belief, creating that idea that you’re not the only one who has this, you don’t want to be the lonely guy trying to pay through you know you don’t want to be the person who’s downloading their music on the Zune when the world has moved on to the iPhone.
And so that’s, that’s, I think where we’re really in danger right now. For a lot of those brands, you have to be really conscious of the vacuum. How do I stay on top of the pile? How do I continue to anticipate those customer needs? And how do I make sure that everybody who uses it is happy, using it to the point that they tell their friends, this is the one. This is the one that you got to have. This is the only one I want to pay you on from now on.
Suresh:
And I think, you know what you’re talking about is fascinating. You mentioned customers in the context of Backbase and you talked about you know having more users and anticipating needs. In some ways, if you have more data, you can anticipate needs better. And to have more data you need more customers, and is this model leading?
You know and I think it’s a great thing that everybody is trying to grow and say I’ll get more customers. But is this what is leading in the FinTech world, to a very particular thing which is that the race to acquire more data and more customers who can give me more data is leading us to a kind of a path where we are doing things that are sometimes right but also a whole lot of stuff on data privacy and you know how to track people that is not necessarily the nice side of the story. Do you have anything to share on how people are, you know what you see as the dangers of this whole, of this whole side?
Greg:
Yeah well, I mean certainly the dangers of holding data are out there for everybody to see. You know you look at the breaches and how public they are how damaging they are to a company’s reputation, and you know, it’s for a long time, I think there was this idea I want to just try to acquire as much data as I possibly can. I think everybody on all sides is trying to acquire as much data as they possibly could. And then you over maybe the last couple of years I’ve started to see this, this other idea emerges, which is, I don’t want to be responsible for your data. I don’t want to take that on. And so, you know I actually heard somebody at Finovate Fall a couple of years back having a conversation and saying how long do I have to keep that data before I can get rid of it? Which is a question that I never in a million years thought I would hear. But from his standpoint is like data is a liability for me. You know I’m not in the business of holding data I’m not trying to analyze it, I’m not trying to use it for AI, I’m trying to use anonymized data and then move on. And I want to just have everything be as, you know, I want to hold as little as possible.
And so, I think that’s really the question that everybody needs to be asking themselves right now. Do I want to be in the business of holding data? And if I am, what am I doing with it that’s going to make that worthwhile? Because there’s massive risk associated with it so there has to be something else on the other side to balance that risk out. And if you as an organization, don’t have a plan for you know I want to use this data to do this you know we think we can build something new we can plug it into an AI algorithm and have it do something fun for us. Then, if you’re not able to find value there, then I think, the motivation is actually on the opposite side to try and hold as little data as possible. Try and keep it you know under in cold storage, keep it away from any possibility of getting hacked, because the potential downside is very real. And there are financial brands that really struggle to recover and to regain trust after an episode like that, and they live long in the memory.
You know, I think, as consumers, when you hear about something like that, it leaves a scar, and you can hear somebody mention it and company, you know, even now, when somebody brings up Target and this is many years old at this point, I still think of the breach that they very publicly suffered and through no real fault of their own. And again, they’re not in the position of holding data that wasn’t something or trying to do but they, they got really punished for, you know, through from a variety of areas for making that mistake so you know for me I think that’s really what it has to come down to, you know this question, what are you doing with the data to make it worth holding it? Because if people say data is the new gasoline and that’s true, but gasoline can explode. So, you got to be really careful, you got to make sure you know what you’re doing with it.
Suresh:
You know, that’s such a fascinating thing because I’ve never thought about it like that I always go and ask CEOs and all that and they say oh we have a lot of data. I said what are you doing with the data? Are you getting any return on that data? But I think you are also bringing up a very fascinating thing. There is a cost to holding data and there’s a cost of not just, you know of compliance, the cost of the explosion and the inside nuclear fuel in a way, right? So, and I don’t think people talk enough about that but you know that’s probably a podcast by itself.
Greg:
Yeah.
Suresh:
I’m just going to go a little bit, a little bit into some of the things you mentioned. You started off the beginning by saying the algos you don’t see, and credit scoring is one of those things that consumers don’t see but it affects our lives in fundamental ways, right? I mean you know your FICO score in the US is something that pretty much determines what you will get or not get right. And as you’re seeing more and more AI that’s being used for credit scoring you know. loan available eligibility, the personalization of the option whether it’s the interest rate the turnovers, etc. And the two kinds of emerging consensus out here, and both are probably true.
One is that it’s faster, it’s more accurate, it actually enables more people to get credit. On the other hand, it’s biased and it perpetuates the existing bias of the data set, or the individual doing that. So, what’s your take on where AI, you know, the utopian credit future the dystopian credit future whichever it is any examples you can share, any idea where AI is going to take the lending business?
Greg:
So, I think I’ll start by saying I think we’re already in a dystopian lending situation. I think that the situations that we have and the way that we look at creditworthiness is fundamentally flawed, and it’s archaic. It’s based on things which don’t have a huge amount of relevance. If you look at credit scoring as trying to answer the simple question: will you pay us back? And that’s really what it is. It’s trying to answer this basic question: will you pay us back? And I think if you look at the system that we have in place and you look at your recent history, it’s not too hard to say that we do a really pretty bad job of anticipating, who’s going to pay us back right? This is, you know that we and we sort of just accept this we accept this risk that it exists here we accept that, you know, we can do the best we can but we still know there’s going to be, you know X number of defaults and we build that into all of the models and everything like that. And I think this is where it gets really difficult for banks to move beyond that because you know that knowing a system is broken, is one thing, replacing it with a system that’s better, is another thing altogether.
From my standpoint I look at what’s possible now from an artificial intelligence capability and you see people who are applying AI tools towards this question, will you pay us back, and they’re looking, they’re able to find a huge number of metrics, which are much more closely tied to how likely somebody is to pay you back, that are virtually ignored by the current credit scoring systems.
Suresh:
Could you share some examples, Greg? Because this is so fascinating you know I liked what you said. I till now thought that the system of credit scoring was what it is and it is okay. And you just described it as dystopian, not a lot of people do that. Everybody thought it was utopian. So, I’d love to get into a little bit more specifics on what do you think are new ways in which people are actually finding out these metrics. I mean, it’s such a fascinating area.
Greg:
Sure. So, I mean if you look at what the current credit system does, it ignores massive portions of the global population. People who through no fault of their own are just categorically excluded. We’re blanket denying huge swaths of the population, you know, inside the US, there are massive numbers of people who struggle to establish credit because they don’t have somebody who can sign on to that first credit card. They don’t have a cosigner somewhere, right? This is one of those areas where, you know, if you, if you have a privileged background, your parents can help you establish credit at an early age and you’re off and running. You know you can get, you can start to, you know, get this documentation, this credit history going really quickly. If you don’t, it’s so difficult to catch back up.
And so, you know there’s a company that has won Best of Show a couple of times at Finovate called Neener Analytics, who really looks at this question, are you going to pay us back? And what they’re finding is that they’re able to dramatically expand the types of people that a bank can safely lend to without incurring massive amounts of additional risk by looking at other factors, and the ways that people answer, you know, fairly common questions. And so, you know, I think I will be the first to say I don’t, I’m not privy to exactly what’s going on in the background exactly how that algorithm works. But you know they’re able to look at a lot of people that the current credit system blanket ignores just blanket denies and are able to make this, this group available in dramatically expanding a bank’s potential customer base. But more importantly, getting people to a point where they have access to the basic banking services where they can start to do things, you know you when you get your paycheck that you can actually deposit it without losing 7% to a check casher or if you need a short-term loan, you can do it at a rate that’s not, you know 33%.
So, you know, and I think I want to come back and just kind of defend my dystopian statement a little bit more, you know, if you look at the population of the world right now, and you think you know what percentage of them are potential customers for banks? Do you think it’s more than half? Do you think more than half of the global population is a potential lending risk? Because I don’t. I, and if you look at that system on its face and say you know and I’ll be clear here I don’t have data that suggests you know that this is kind of based on gut feeling. But, but if you look at and say and we have a system right now, where there are literally billions of people who are prevented from accessing any credit whatsoever, that to me is a major problem. That’s, that’s a gigantic problem that needs to be solved. And if you come to me and say you know I can tell you right now that no one in this group of let’s, be conservative, let’s say 2 billion. When no one in this group of 2 billion is trustworthy none of them are going to pay us back. I’m calling you a liar. I’m saying there’s no way that that can possibly be true.
And given that you know we have a system that you’re really dramatically, dramatically overvalues where your parents have come from, and your creditworthiness of the people in your life dramatically undervalues how creditworthy you as an individual are. And that to me is where there’s a really significant problem.
Suresh:
Greg, it’s so fascinating to listen to you in fact I don’t think your dystopian thing needs any defense. I just felt when you used it shifted my mind immediately because we tend to take the system for granted and say well, this is disruptive, but actually, it’s not. What you’re saying is the present is not actually right. And anything that can improve that is better, and, and it’s, it’s, it’s such a good example of how AI can do good for the world. Because here it is I mean the risk is always measured through data accredited decisions using data you’re saying people are using alternative forms of data to make that lending decision.
And to me, it’s one of the great uses of AI if I can actually find that, and also develop models I guess you know today nobody has a model to say if I lend 100 you know, to 100 people in this group, will they pay it back? So, you need to start the process and I think that’s what you’re describing. Greg again, you know, conscious of the time out here and I want to talk about something that you mentioned, I’m going to go back to your son, and social impact and purpose as you call it right?
Another fascinating use of AI that we’re hearing a lot about and you know just want to get your take on it. You know, obviously, you know, ESG guidelines are becoming very important for companies worldwide and now there’s apparently a machine learning algorithm that can measure whether a company is meeting its ESG standards. You know, hedge funds are starting to say, are you going to be, you know, having a positive impact on the world and so on. What do you think of this whole use of data to actually measure things like purpose? And where do you think we’ll keep going?
So, I think, what do you think of this whole thing where ESG standards are being, I mean data is being used to measure whether you’re actually doing good for the planet.
Greg:
So, I applaud the idea. I think that it’s a really good idea and I think it’s good to start looking at the actual metrics, something that you can quantify and really get to demonstrate how companies are doing when it comes to fulfilling their promises in these areas. Now that said, I think the real challenge comes from the idea that you know what is good, right? This is something that is going to be a different definition for every individual. And, and my concern is that if you look at something, you get this type of governing body that says you know we can have this data that says you actually no you’re, you’re good, you’re doing what you can do from ESG standpoint. That is, there’s a real danger that it ends up, limiting the upside.
If you get kind of if you establish a minimum bar, then a lot of companies just have to get over that minimum bar and we lose the companies who are really going, for it up top. And so, but I think when I look at it, this is something which I think people feel on a personal level, you as a customer have a view of the organizations that you work with, and you how socially responsible they are to you might not be how socially responsible they are to somebody else depending on a wide variety of factors. So, you know, I think that it’s a really personal piece. Now, I haven’t spent a ton of time studying this tool and what’s possible if it really is able to kind of push everybody to get to a minimum bar and, and it’s, you know, gives us this kind of data than great. I just hope it doesn’t turn into one of the situations you know we’ve seen the way this has kind of factor when it comes to like environmentalism in the past when their various licensing agencies that say no, we certify this as a green product. What does that mean? You know, what is a green product exactly? You know, this is carbon neutral, again this is all getting into this thing and how do you really delineate that…
Suresh:
Again, you know I’m going to go over and I think you know going to go back to your idea of your son and you know the way you started this thing about Finovate. Why wouldn’t companies let the customers actually decide what is good and let them vote for it? Because you know, again, you looked at what you said about, in the way you do matchmaking today.
If your son is a customer and there are millions of them who want to support the panda. Shouldn’t he actually be saying you know I could do this? You don’t need another body or a standard necessarily, right? We should be able to find a way where data is actually used to guide some of the decisions of what is good because what is good is what people around the world think it is.
Again, I think that’s probably another rabbit hole that we could go down to but Greg just to wind up I think we’ve talked about, you know, where Fintech is going, where are you seeing, you know, banking, the industry going, and a few keys AI-led innovations, any one or two big predictions where you think data and AI is going to take us in the next, let’s not worry about 10 years, let’s say in the next three or four years?
Greg:
Sure, well, I think. And that’s a great place to end it you know. And so, from, from my standpoint, I think it was maybe 2016 that I saw the first AI play on the Finovate stage. The first like kind of purely AI play, and then by 2018, you know, in my kind of back of the envelope math, it was about half of the demoing companies were using AI in some way. And there was this shift away from the kind of, we can use AI to, we are using AI to solve x. And I think that’s a really important shift in the industry because the AI at its core is really just a tool. It’s not a result in and of itself, it’s a path to a result. And so, I think that you know the future of the industry as it relates to AI is going to be application-based it’s going to come down to where there really are problems that need to be solved. Where it makes sense for AI to get involved. And the honest truth is it’s probably going to become an ever-present, it’s going to underpin just about everything that we see.
And then, of course, the question becomes, okay well, where will that data come from? That feeds into it because that’s a really crucial piece of the equation and flawed data produces flawed AI and there’s a really clear line between these two things. If you put biased data in you get biased AI. There’s no shortage of amusing stories about AIs that have been trained to act badly in any number of different ways. The hard part is coming up with one that’s you know, bias-free. If we get the right data set, I suppose we could imagine that happening, but at the same time, I think you know this is really what’s going to define the success of these AI plays: the quality of data that you have, the ability to understand and clean and make this data usable is going to be extremely important and now we’re seeing at Finovate the number of companies that come up and start to support these ideas that say you know we can help you take the data that you have and make it more usable.
I think there’s going to be more of these kinds of data support, data cleaning types of plays because I do see AI I think really underpinning a huge amount of different types of technologies over the course of the next couple of years. I mean it’s already happening. There’s maybe, maybe we took a little bit of a step back during the pandemic where people focused on some more, urgent problems, but I don’t see any reason that you know this trend is not going to continue. And I think pretty soon we’ll be you know companies that don’t use AI I think will probably be in the minority to some extent. When you get to the point where event organizers are using AI, then everybody is using AI, at the end of the day.
Suresh:
Hahaha. No, but I am looking forward to the day when your son turns 18 and he’s able to not even walk to the bank but they’ve anticipated everything and they say here it all is. We know what you need to do and we know and kind of provide you all of that service on your smartphone or a little biometric chip. It is probably going to come. As I said, we can continue talking about this, and I am sure we will have you back on the show again.
We have Greg Palmer, FinTech columnist, podcaster, Vice President of the Finovate Group. A connected man who makes connections in the world of FinTech.
Thank you very much Greg for being on Slaves to the Algo.
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Thank you once again Greg for being on the show and see you all next week.
Thank you.
Greg:
Yeah, my pleasure Suresh, thanks for having me.
