By leveraging the same FCRA-compliant data used in traditional underwriting through the lens of an advanced model, Partners who plug into Pagaya's vast data network can serve more of their potential customers, drive growth, maintain a seamless customer experience and deepen relationships, all while mitigating risk, with no incremental costs and without sacrificing business growth.
Key Learnings:
- Why embracing financial inclusion can help your bottom line
- How new technologies, such as AI, can transform traditional lending/underwriting models, leading to increased access for underserved populations
- What a fintech-bank partnership can do to drive a more inclusive financial ecosystem
Penny Crosman (00:07):
Welcome everybody to this lunch. We are going to focus on financial inclusion, why it matters, how banks can make money off of being more financially inclusive, what some of the latest AI techniques can do to help improve access to credit and how bank FinTech Partners Bank, Bank FinTech partnership can help in these efforts. So I am happy to have with me Leslie Gillin. She is Chief Growth Officer at Pagaya. Okay, good. She formerly worked at some major banks. She worked at JP Morgan Chase, Citi Bank of America at MBNA, and we have Liz Pagel who is senior vice president of consumer, the consumer lending and consumer lending business lead at TransUnion. And before TransUnion, she was a principal on the financial services team at Boston Consulting Group and she began her career as a credit underwriter for JP Morgan's commercial lending business. So delighted to be with you both. It's super interesting topic. Oh, and I'm Penny Crosman. I work for American Banker and we're putting on this conference, and if you don't get American Banker, you should, it's a news publication. We cover all aspects of financial services, including FinTech. So maybe you could share with us from sort of a personal and a company perspective, why do you care about financial inclusion? Why does it matter to you and why does it matter to your company?
Leslie Gillin (01:54):
I feel like I'm in front of Congress. So it's great to be with all of you. I've spent 31 years, I always say I started when I was seven. I spent 31 years in financial services and just had a lot of really good experiences. And my most recent job at JP Morgan Chase before coming to Pagaya, I was chief marketing officer of JP Morgan Chase and it was during the time of George Floyd and during COVID and we all can remember that. And so that moment, even though I had been in financial services for 30 plus years, and by the way there's a lot of amazing people who work at banks every day, day in day out that are trying to do the right thing. But it just amped, it just took it to another level in our consciousness to just admit we have systemic challenges in this country and we need to do more faster. And I just happened to be in a role that when Jamie put the 30 billion in the path forward down that it just, it's just like we all know how important it is, but it amped up the fact that there was a mandate kind of on the table and then the business roundtable got involved. And so I just had a great inside track that even though I was always in marketing roles for a very long time or product roles and I've been in lending my whole career and that there have been CRA requirements for banks and then inclusion focus, besides the fact it's just good business and just being part of having a diverse population within your employee base and then serving because you need to reflect the consumers that you're serving. I just had that opportunity to always be in the day to day. And then when I had the opportunity to come to Pagaya and I realized how much more can be done with data in the partnership that we have with TransUnion and we'll talk more about that. Basically now I am spending all day every day seeing the fruits of the labor in a much bigger way. And so I'm just excited about the fact that we can make a bigger impact on the overall banking ecosystem with what we're doing at Pagaya today.
Penny Crosman (04:32):
Just a quick follow up. Did you say 30 million in that push forward?
Leslie Gillin (04:37):
Billion.
Penny Crosman (04:37):
Where did the money go?
Leslie Gillin (04:39):
In the path forward? So it was a combination. It was a five year commitment and it was across a small business consumer really focused on black and Latinx. And so it was a combination of lending across all of the lending verticals. And so working with LMI communities and so there was just a litany of different programs, but it was all focused on black and Latinx and progressing that forward.
Penny Crosman (05:16):
I Just always, you know, always see these announcements. A big bank just invested 30 billion and something and then you always wonder, can I get the follow up analysis of the audit of where exactly the money went and what happened?
Leslie Gillin (05:28):
I mean what would tell you is nobody's going to put 30 billion without knowing that they're going to get that follow up question. So there's definitely a lot of auditing and opportunity there.
Penny Crosman (05:42):
Alright. So Liz, why do you and TransUnion care about financial inclusion?
Liz Pagel (05:47):
Yeah, so I also have been in financial services for my whole career and as I've left consulting I wanted to think about where can you have the most impact across consumers and the value of data in bringing financial inclusion. We'll talk about this with Leslie as well. The enormous amount of data that a credit bureau that TransUnion sits on that can help deploy out into the market to help more consumers. I mean there's 60 million underbanked consumers without credit scores in the United States. How do we bring more data to more consumers? How do we underwrite better with the tools that we already have today? There's a ton of opportunity there and if you ask TransUnion, we've got a strategy on a page that came out about a year ago and the number one thing that we're trying to do is financial inclusion globally. You ask our CEO you ask anybody, that is our goal. It looks very different across different markets in India versus the us. In the US we've got such an amazing data asset already that we're just adding to and bringing in more innovation. And in my role I work pretty much exclusively with the FinTech's and with banks that do unsecured personal loans. And that's where the innovation is. That's where all these exciting things are happening, about how we use the data better, how we think about new types of data, how we can bring more data to the market and in order to have the most impact in my career, having that ability to influence across the whole market, how the data's used to help lend to more people and help grow that American dream and grow people's ability to access credit. It's a powerful position I think.
Penny Crosman (07:22):
So I know we want to talk about what is the state of financial inclusion today? You mentioned the 60 million people who don't have credit scores. Why don't they have credit scores?
Liz Pagel (07:34):
Well, I think that there's an interesting movement right now where people are becoming more, I kind of credit Karma started this more conscious of what a credit score is and what it means and how to build it. And in the past, I mean people would graduate from college, use debit cards after, especially after the card act when you no longer got a free blanket at the football game if you applied for a credit card and it was cold out, which is how I started my credit.
Leslie Gillin (08:00):
Which was my first job, I was actually at the table handing out the blankets.
Liz Pagel (08:06):
But a lot of people don't understand how to build credit, so you need to have credit to build credit. And there's a lot of new products out there. I mean, credit builder products are a hot topic right now. If I counted the number of companies coming to me saying, I have an idea for something that's going to be a credit builder, can I report this to the file? And I say no, but maybe change it a little bit and make it more like credit. And yes, we can and we can help consumers get into that credit ecosystem, but you know, have to start somewhere. You have to start with a secured card oftentimes, and it necessarily make sense that you have to put money down in order to use a credit card. So continuing to help consumers understand what they need to do to start and build credit over time. There's a lot of companies like the Credit Karma of the world, the credit of the world helping with that, but I think there's a lot more to be done to help consumers get into that credit ecosystem in the first place.
Leslie Gillin (09:02):
The other thing I find fascinating is the fact that even when you do have a credit score, 42% of people who apply for credit today are the reason they've been rejected is the reason is the FICO score. So even if you do have a score, and to your point, credit bureau is very important and how you can improve your credit and people are learning more about debt to income ratio and how much that impacts in a moment in time. But still to have almost one out two people it be declined for FICO score. And then you couple that with, there's over 6,000 banks in this country and many of them just don't have sophisticated underwriting platforms. And so to me there's just a lot. I think the point is there's a lot of opportunity to go deeper, which is what we do at Pagaya is a second look across auto card point of sale and personal loans and you realize how many people just get missed. In fact, one out of two of what we do today is below 660, but one out of two is above 660 that for just some reason in the traditional writing underwriting platforms and many of them have binary cuts as we all know, if a debt to income is 30% or more, somebody's getting declined in that moment. Well, what we can see is, and we can talk more about that, is that somebody may have pristine history for 10 years but just happens to in that moment have a 32% debt to income ratio and their declined. So the system's not perfect, and I think that's what we're both very excited about in the work that we do is how much information is out there. And it's not just the data, it's like your ability to leverage that data. So it's just as important, the AI and the systemic way you're able to leverage that data and actually see a more complete consumer. And there's still a long way to go.
Penny Crosman (11:13):
So I want to follow up on more specifically how you do that, but just as the, what's the word anyway, just as a counter argument, some people listening to you might say, well, if someone has a low FICO score, then they're high risk and they shouldn't get a loan. So what's the answer to that?
Leslie Gillin (11:34):
Yeah, and you can help me with your thoughts too, but if somebody has a low FICO, it's almost a little bit sometimes like a self-fulfilling prophecy. If you have thinner credit, then you have a higher propensity to have a debt to income ratio. Just you don't have as much as many variables that go behind the FICO score that enables your score to increase. And so many times, to Liz's point there, it's important to have those products that are out there that enable you to increase your credit score over time, but it's really by proving that you can use your credit and that you're paying back on time and that you have a depth of a file for a certain period of time. And so many times people who are the newest to credit or they had one if you had a bankruptcy 10 years ago, many banks have binary cuts that I don't care if you had a bankruptcy 20 years ago, if you've ever filed bankruptcy with our institution, you'll never get a loan again. And so those are things that just, there's so many different examples that's what makes it so complicated. But to me the glass half full is that there is still so much opportunity for people who are credit worthy to be getting credit today and that's exciting is people every day are walking into in branches or they're going online and they should be getting credit that they deserve to forward their ability to live the American dream. And there's a lot more opportunity tools that are out there that banks could be using.
Liz Pagel (13:23):
And I'll add, so FICO scores and vantage scores, absolutely rank order risk. They've been the staple for years and years and years and they work, they truly do. A lot of people are on older versions of these scores. And one thing that both FICO and Vantage are looking at and doing and moving forward is like how do you take the data that we already have on the credit file and look at new insights on it? So if you look at somebody who is a 660, if they were a 760 last year and now they're a 660, that's a very different person than the person who was a 560 last year and now is a six 60. So if you look at what we call trended data and how the consumer is moving over time, if they're falling or rising through the credit spectrum even that is an example of a really, really powerful insight that 660 is not, those two consumers are not the same. The risk profile, I mean, one, you don't want to catch a falling knife if somebody is really on the way down, that's an entirely different consumer than the one who's been working and building up that credit and paying back on time and getting past that delinquency that they had a couple years ago or that bankruptcy that they had long ago. And just looking at different ways to look at the traditional credit data is a ton of power just in that if you're using an older version of some of these scores, you're not seeing, and now lenders today, some that do still use underwrite primarily on those scores are adding data on top of it to see if they're insights that you can glean from putting an overlay on top of those data, those scores just to see, hey, is this consumer moving up, moving down? We've got consumers who've got an alternative credit database with data from consumers who take out high interest rate loans or short term loans, and those don't appear on the credit file. What if somebody has, doesn't have access to credit in the traditional sense right now because of their credit score, but they've actually been taking out super high interest rate loans, paying them back, they need to use that to finance their lives, but they're creating a good track record on another file that you're not even seeing like that's FCRA data. That's additional data that you can use to try and find those consumers and allow them to prove themselves outside of the traditional realm. So there's so much, even when you're still looking at just plain boring old FCRA data, you can find more insights.
Leslie Gillin (15:40):
Well, and can I just add on that on the plain boring FCRA data because there's obviously a lot of, one of the biggest challenges I think we all have in the banking space and the lending space is that, and this is not a knock on regulation, but regulation always lags innovation. And that tends to be some of the biggest challenges. And there needs to be regulation just to make sure that there's there that we're all doing what we should be doing. But at the same time, there's all this opportunity in open banking data and alternative data and such PGA's chosen to only use FCRA data because of the scrutiny of AI and alternative data and other things. And the fact that we can already increase approval rates on DECLINATIONS by 25 to 30%. So my point is even with boring FCRA compliant regulatory data, you can make a meaningful impact by leveraging many, many more variables like the Vantage score data behind a FICO score and be able to make a very meaningful difference increasing originations by 20% approval rates by 25 plus percent.
Liz Pagel (17:02):
And I think that proves the point that there is so much value in looking at the data in different ways. If you are approving tons and tons of consumers that others have declined and your performance is still great. So there is pockets and if you can find those pockets of consumers that are credit worthy and deserve the chance, really exciting.
Penny Crosman (17:23):
Devil's advocate was the word I was trying to think of before. Sorry. So Liz, just to, I'm sorry, not Leslie, just to close the loop on that. Can you just kind of walk us through how you underwrite what the guide does today?
Leslie Gillin (17:37):
Yeah, so think of Pagaya as a network and we have AI that actually in our strategic partnership with TransUnion, we have over 15, 20 years of data in production of all the consumers in the US and then we have pre-funded capital that we bring to the table with all of our institutional investors. We actually started as an asset management company. So we have many in institutional investors, private bank clients, et cetera that are looking for alternative investments and they're able to bet on the consumer. And then what we have is over 25 partners that we work with SoFi or an ally and a number of different auto lenders, et cetera, where we do a second look. So basically the best part of it is there's no difference in the consumer experience. So we plug into their lending platform through a seamless API and a consumer when they are applying, if the lender is going to decline it, they pinging our API and in milliseconds will come back to them and say, we recommend to approve, here's the pricing, here's the loan amount. And then they can make that approval and they keep the consumer. So for a customer who's working with or approve applied with Ally or Best Egg or SoFi, they can or Klarna credit with point of sale, they're that consumer, they don't know because Pagaya is a B2B, B2C. And so we're enabling that decision making capability, that model. Now, what's also good about that from a bank or regulatory perspective is our model follows the exact same model validation model risk management, fair lending practices as if we built that model inside of a bank. So because obviously we wouldn't have a business or we wouldn't have partners if they couldn't pass the regulatory scrutiny of model validation. So we basically leverage many, many more variables behind the FICO score in our AI and we have all of our partners and then we have the institutional investors and we basically are enabling those partners to go deeper by saying yes to more consumers. And then the best part is that partner is keeping that consumer and the institutional investors are buying those loans in daily cash settlements. So basically the partner doesn't have to take on any incremental risk on their balance sheet. And the last thing I would say, what's exciting about that is a top three bank in this country, I was talking to their CRO and he said, so basically what you're telling me is that you're going to pay me to do your AB testing, meaning tomorrow currently declining people, but he could actually approve 25% more leveraging Pagaya, but yet not take hold that risk on the balance sheet. And they can accelerate their ability to improve their models because they have that servicing data. So it's why I got so excited about coming to AYA because it's a fascinating model and it basically enables the consumer to have the product that they wanted with the brand that they wanted to do business with. It's not a second look where you're selling declines and then it's a bad experience for the consumer and they're getting a price point they weren't looking for in the first place. And that's exciting about what we're doing.
Penny Crosman (21:14):
And Liz, what have you guys been doing at TransUnion to promote financial inclusion?
Liz Pagel (21:19):
Yeah, I mean, so there's a whole lot going on right now. I think it's a really exciting time to be at a boring old credit bureau, but there's so much I talked about alternative credit data coming from short term loans. We're doing a lot with cashflow data, building attributes on top of data that gets scraped or pulled from banking data. I think that cashflow underwriting will be an enhancement to underwriting for the future and really help again, more consumers, especially that thin file consumer get access to credit. We're also working on income attributes. We're working on telco data rental data. There's just so many treasure troves of data out there that we can get into the hands of consumers and make sure that data is regulatorily approved and the lenders know how to use it. And then I think we'll get to this later, but the thing I'm most excited about that my team is working on is getting buy now, pay later data onto the credit file that can geek out about data. But that is the biggest data set that's just sitting there with a relatively small number of lenders. They have it, they've got it in place, they could start reporting it as soon as they're ready. And the most exciting thing for me is they want to, so that's just sitting there ready for the taking.
Leslie Gillin (22:39):
They want to, going to have to at some point
Liz Pagel (22:42):
If I have anything to do with it, but regulators, there's a lot there and a lot that we're moving towards.
Leslie Gillin (22:48):
And that's exciting because that's the fastest growing asset class from a lending perspective. So 35% of the US consumer base has already used point of sale.
Liz Pagel (22:59):
May be even higher.
Leslie Gillin (23:00):
Yeah, maybe even higher today. So it's a necessary data trove to your point to be able to round out a consumer again. So there's only a good guy to be able to have that incremental data so that those consumers are actually showing more history. And now that's another example of having that history brought in so that more people can get approved.
Penny Crosman (23:22):
So for the buy now, pay later data, are you basically getting, are all of the providers giving you data like Affirm and Klarna and all the others?
Liz Pagel (23:33):
So it's complicated. This has been a long journey. I remember when the first meeting I had at TransUnion about how to get the buy now pay later data was in a conference room in Chicago, in person pre covid. So we've been on a long journey trying to figure it out because at first glance it looks like a installment loan, right? It is an installment loan, but it's short. And consumers use them over and over 3, 4, 5, 6 times a year. And if you added six installment loans to the credit file today, the scores, the advantage and the FICO and everyone's custom model would probably tank that consumer score. We have attributes in there like average age of trade that don't anticipate a consumer using any product six times a year. And the lenders want you to use the product that often. If I think about my credit card, if I financed everything in the past year that was over 500 bucks, I'd have a couple of loans on my file and that would not do good things for my score. And that's how it's intended to be used and it's going to be powerful data. So you can't jam that square peg into the round hole of an installment loan. So we've worked with the lenders and agreed with them that the best way to do it. And for financial inclusion purposes, we really do want that data on the core file. It could go on an alternative file and sit there and wait for somebody to decide to use it. But so many consumers, like some surveys say up to half of us consumers have used buy now, pay later. This is a mainstream product. This is not something that belongs on an alternative file, it belongs on the core file. So I've worked with all of the point, the big point of sale lenders, I've worked with the regulators and we have decided to put, and the other bureaus have agreed to put it on the core file, but tag it and partition it away so that nobody starts ingesting it. If you use data, you don't ingest it unless you turn it on. So it gives the whole industry time, including FICO, a Vantage who are very excited to incorporate it, to adjust their models, to not treat it like an installment loan and then to build new models or enhance their existing models. And the best thing about it, it's a more straightforward way to tell consumers to build credit. So if you say like, Hey, go finance that pair of sneakers, make sure you can pay for it, but finance the sneakers and begin to build credit, that's a little bit more straightforward than say, trying to explain a secured card.
Penny Crosman (25:54):
Alright, well thank you so much Leslie and Liz. I think we're just about out of time. Thank you all for coming to this lunch. We're going to start with the main conference of content in the general session room at one o'clock. So see you guys all there.
Leslie Gillin (26:09):
Thank you.