Hi Guys, welcome to the Fintech Coffee Break, I’m your host Isabelle Castro.
While at Fintech Nexus’ USA conference, I sat down with Lauren Crossett, CRO of Pinwheel, before Day One to talk about alternative data and how it can impact people’s access to credit.
Pinwheel focuses on providing access to income and payroll data, allowing financial institutions to use a broader view of a client when making decisions on credit. This can help consumers usually excluded from the credit system, to access loans, credit cards, and other products.
Isabelle Castro – Hey Lauren, how are you?
Lauren Crossett – I’m doing well. How are you?
Isabelle – I’m good. Thank you. Well, we’re here at Fintech Nexus USA Day One. Are you excited?
Lauren – So excited.
Isabelle – What are you most excited about?
Lauren – I love conferences like our team gets so many great conversations with so many people in one place at one time. Like, it’s awesome. I’m excited to see what the pipeline looks like on Friday.
Isabelle – Nice. Okay, I’m really excited. So to begin with, what gets you up in the morning?
Lauren – Yeah. This is like literal, and, and broader. But my daughter, so she’s almost two. She’s definitely the alarm clock in the house, and our dog. But they’re also like, why it’s exciting to get up and play with them. And we always go out for a walk. And it’s a great way to start the day.
Isabelle – That is a lovely way to start the day. Definitely. So tell me about your journey coming to Pinwheel.
Lauren – Yeah, so I had been in traditional financial services. And then through meeting people and different kinds of coincidences, I was a really early employee at Quovo. And we did connectivity to investment accounts, as well as bank accounts. And then I was there for a while, and we became like, pretty fierce competitors with Plaid. Ultimately, Plaid acquired us. So I was at Plaid for a few years, which was great, you got to actually see both sides of the competitive space, and learn so much. And while I was there, a lot of people continue to ask like, Well, what about payroll connectivity? Like, when’s that coming? And at first, I wasn’t super excited about the space. But the more I thought about it, and the more I heard customers and prospects talk about it, I was like, Okay, this is cool, I need to get involved. And, and so I met with all of the different players in the market. And, you know, Kurt had a really broad mandate, and was really excitable and such a strong leader. And I think that’s a lot of times what you look for, and when you’re going to join at an early stage, like, is this gonna work? And, so yeah, he was awesome. And I joined, I was able to build out the whole go-to-market team from scratch, which was also really important to me.
Isabelle – That’s nice. So Pinwheel focuses on simplifying income data for fintechs to use, right? Why the focus on income data specifically?
Lauren – Yeah, so it’s a little tiny bit more broad. And that is connectivity to income or payroll data. But the the focus is like, that’s such a major, you know, top of the pyramid of someone’s financial life, where they’re employed, that’s how they get paid. And so it’s like such a huge piece of the puzzle that is really, like, not been cracked. So it’s just so many possibilities from actually having that information made available. And then we try really hard to also answer the questions that our customers are going to have relative to that data. So not just like, how much did someone earned last year on their W two? But like, how much have they earned this pay cycle? How much do we expect them to earn in future pay cycles? When do we expect them to get paid? And those are really important pieces of the of the larger puzzle that lenders and financial institutions can use to offer better services and products and advice.
Isabelle – It sounds like it could have quite a big impact on financial inclusion. Tell me about this aspect to alternative data.
Lauren – Yeah. Well, we certainly hope so. I mean, like the current credit scoring system just doesn’t include income. And, you know, we did a survey and seven out of 10, respondents said that they would want a credit score to include income. So it just makes sense that it should. And a lot of that reason is because the traditional scoring system isn’t necessarily about someone’s ability to pay. It’s about their historical payments and lots of other factors as well. And so simplifying it to just this is the inflow, look at the outflow and see their willingness to pay is really important.
Isabelle – No, I agree. I agree. It must give a whole kind of worldview of the person right instead of just this. So how do the companies you work with usually tend to use this data?
Lauren – Yeah, so it depends. We have a lot of bank customers and neobank customers that use our connectivity to do things like allow for simplified direct deposit switching. We have a lot of banks and fintechs, and lenders that use data for verification of income verification of employment. And then we do have folks using the data to actually make decisions which is like the best part. Well, not to diminish any of our other use cases. Our customers but in terms of advancement of financial services to be different and to look different, I think including payroll data and income data, and in part of the decisioning process is really important.
Isabelle – Yeah, no, I agree. I mean, Pinwheel released a study late last year looking at customer attitudes to credit scoring. Tell me about some of the key findings in this.
Lauren – Yeah, well, I mean, it’s not earth shattering, like the system is broken or inequitable is more appropriate. And consumers are unhappy with the traditional scoring system. So nearly eight in 10, respondents agree that credit scores should not be the only criteria in getting a loan. And I already mentioned that income is something that folks want included in determining their creditworthiness. And also, like, maybe, notably, a lot of consumers. And I think it’s yeah, like 80% of consumers that we surveyed, were open to sharing that data, too. So they’re like, just give us the opportunity to make income and in our employment information available and part of your decision-making process. And, and also, it’s, it’s not, I guess, not obvious, but these people are still having to borrow funds. And so they’re going to their family and friends. And they turn out to be like, pretty great borrowers. And so, you know, our customers are missing out on those customers, because of the system. I guess
Isabelle – It can turn into quite a difficult cycle for them, if they’re not included in the system, like with loan sharks and all that kind of stuff. Yeah, you guys are changing lives.
Lauren – I hope so. And we talk to our team about that a lot. We aren’t offering direct-to-consumer products that we have the great pleasure of being able to say, by making data more available and by answering difficult questions, how can we ensure that our customers can make their products more inclusive. And it’s really obvious for things like earned wage access so that people don’t have to go that payday loan shark kind of way. And it’s certainly important for just like, expanding the credit box, it’s definitely probably the first place to start. It’s just like chipping on the sides of that to expand it. And so, yeah, it’s really fun to see as we continue to make progress in that arena and get lenders comfortable with a new means of looking at things judging things,
Isabelle – Yeah, that’s great, because alternative data is quite difficult to collect rate is quite messy. That’s what I’ve heard.
Lauren – Yeah, it can be unstructured, it could be that there’s not a ton of historical information, it’s difficult to back test. Often, when you’re like an alternative data provider or trying to sell into a lender, even if they want to use your data, it may take them two years to really start to fold it into their system, because they have to adjust how all their processes work internally, they have to take small samples to understand what is the high-end risk, what are their losses? How can they potentially, you know, adjust things a little bit here or there to decrease those. And so we are hoping that we’re taking some of that work off their plate by making the data not just obviously structured and clean but also taking it a bit further with our data science teams to try and answer the questions that we perceive they will have to answer. And to shorten that cycle.
Isabelle – Okay, nice. So it’s streamlining the whole process.
Lauren – That’s the goal.
Isabelle – Great, good. What, for you, personally, are the most concerning areas of the current credit approach? Like the FICO score and all of that?
Lauren – Yeah. Well, I guess I was thinking about this this morning. There’s kind of three parts to my answer. You know, personally, I think it’s always important to think of your own experiences like I was in my 20s, I was, you know, didn’t have a ton of cash flow and lived in New York, and I would forget to pay spectrum or what have you, and like, you know, you, you make a few mistakes and your credit score gets pretty hurt. And if you don’t have the luxury of just like putting everything on auto-pay, like you have to also find time to deal with that. And so then I think of like, what if you were like a single mother and you’re, you’re working and you’re taking care of your kids, and then you also have to figure out when you’re gonna sit down and decide which bills you’re going to pay when to make sure you don’t, you know, overdraft and that’s a whole other terrible story. So I think, you know, that part’s really scary. There’s just such a big opportunity basically to make mistakes and then have to claw back from it for so long. Even if you get a great job and, and things really change for you. The financial system doesn’t just like unlock overnight because of that score. him. So and then also like, I have a lot of really close friends that aren’t from here. One of my really close friends is from Australia. And I would imagine this would be like, similar for you if you were going to be here with more long term, but like, it’s so hard, you know, she got here with a great job, but having to navigate our credit system or get an apartment in New York City is 10 times more complicated.
Isabelle – Yeah, it definitely is like, I moved to Paris. And I remember the whole process with that it was hard. So yeah, I can imagine America. Oh, another thing. So credit scoring, is there for a reason, though, is there a chance that this alternative data is opening out credit too much and runs the risk of kind of getting already vulnerable people into a kind of a cycle of debt?
Lauren – Yeah, I think that’s always the hard question. Right. Like, you know, a lot of by now pay leaders have come under fire for like, how helpful are they or aren’t they? You know, I think that’s hard. And one thing I do wish is just like, in the, whatever, 10 years, and in FinTech specifically, I really wish to have seen more driverless money, just like making it simpler for people so that they don’t have to make those decisions. Because education on finances is like something you have to be interested in. Yeah, like, it’s pretty boring. And not everyone is interested in just like getting in the weeds and learning it. And so, you know, I think that’s, that’s really hard. Because how do you educate people that like, yeah, you might you may want that thing that you can buy over time? Or that you could get a loan for it? Or maybe you need that thing. But then how do they really understand what the consequences may be? So I don’t know that alternative data really is the thing to point to, I think, you know, as I referenced, companies take a really long time to look at new datasets and to decide what they want to use in their decisioning process. So I don’t think that like alternative data, as its itself as a standalone thing is, is the issue to like increase potential loss rates? I think it’s if people rush into it, or if there isn’t enough back testing. Or if for whatever reason, the data has like poor signal. Certainly that could lead to more risk. But you know, I think it probably is outweighed by all the benefits that looking at additional factors or different pieces of information provide.
Isabelle – No, that makes sense. I mean, it is a whole kind of industry approach to this kind of issue. Right. And we shouldn’t be stifling innovation in that to do it.
Lauren – Right. I think that would be such an easy way out to say, well, this is how we’ve always done it. And there was a reason for it, like, okay, but there’s a reason why it doesn’t work for everybody.
Isabelle – Exactly, exactly. There’s issues with the current status quo. So yeah, there’s room for improvement. What is your opinion on some of the challenges that alternate? What are the most challenging things about alternative data? And how can fintech,s the fintechs that you partner with and your clients, How can they work to go around these challenges?
Lauren – Well, I think it’s easier for fintechs. I think for our bank customers and more traditional lenders, it’s much scarier because, you know, they’re always looking at regulation, and like, what does the CFPB think and? And like, are we going to get a fine that we didn’t expect? For doing something that we thought maybe is the right thing? And believe me; I’m a big proponent of the CFPB. It’s not to say that I don’t think that they should have oversight. But I just think that, like, oftentimes, the easy path, especially for major FIS, is to point to like, this is how we’ve done in the past. And this is how we know that we’re staying within the lines. But, you know, in my experience, regulators are great, and, and people that we want to spend more time with that we can build a more open and diverse system of information that we use for decisioning. So you know, I think it’s the biggest challenge is just that it’s different.
Isabelle – Okay, okay. Yeah. I mean, fintech in general seems to have this, or innovation, I should say, has this kind of thing going against them that it’s different. Yeah. And people have to get their head around it, right.
Lauren – Yeah, exactly. I think we’re moving there. It will be okay.
Isabelle – Yeah. So what’s a piece of advice you’ve been given that you would be that you would give to someone else?
Lauren – Yeah. So I think especially as we think about out people that are treated unfairly within the current financial system. It just reminds me that I should use platforms like this to tell other women like to understand their worth, and to ask for what they deserve and to be vocal about things like raises and opportunities and promotions and taking on more responsibilities. His you know, that is the thing that comes to my mind like, oh, my gosh, what if I were, I had my daughter and had a different financial situation. And that definitely could be the case if I didn’t really have women surrounding me that were helping to push me and to let me know that it’s okay to ask for more. And to understand what I bring to the table.
Isabelle – Yeah, no, this is something that I’m very into, like women pushing other women and having like role models within the system. Right to really go after as a goal.
Okay, curveball question. You’re nearly at the end of the interview. So I went to see a Yankees game yesterday, because I’m in New York, right? Have you? I don’t know whether you’re into baseball. But I learned that each player has a kind of theme tune when they come up to bat.
Lauren – Right. Okay, I’m learning
Isabelle – Okay. Apparently, this is what happens. What would your theme tune B if you were going up to bat?
Lauren – Oh, my God. Wow. The era’s tourists are going on. I feel like this is a Taylor Swift moment. Okay. There’s that one. That’s like, if I were man, yeah, you know that one? Yeah. I’m not sure that that’s the song’s title, but that’s the one Yeah.
Isabelle – Nice. Okay. I like that. I like that. How can people get in contact or follow you?
Lauren – Yeah, I’m Lauren Crossett, CRO pinwheel. So I’m on LinkedIn. And my email is just email@example.com. And I have. I guess I’m on Twitter, but certainly not active enough to reach me there.
Isabelle – Okay, cool. Well, thank you so much for making the time to talk to me. Enjoy the event. And yeah, have a really good rest of your day.
Lauren – Awesome. Thanks, you too. Thank you.
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