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The resources that consumer lenders have to work with today are better than ever before. Gone are the days that risk officers could just pull a bureau file and have access to the best data about a potential borrower. The credit infrastructure tools today are more sophisticated and predictive, allowing lenders to serve more borrowers without expanding their credit box.
My next guest on the Fintech One-on-One Podcast is Misha Esipov, the CEO and Co-Founder of Nova Credit. They are at the forefront in this movement to bring more and better data to lenders and have become one of the leading credit infrastructure companies. I last had Misha on the show back in 2017 when they were just a startup, so a lot has obviously changed since then.
In this podcast you will learn:
- How Misha describes Nova Credit today.
- Why they decided to move beyond the Credit Passport products.
- The performance of the Credit Passport borrowers with American Express and others.
- How the Credit Passport works.
- The history of Cash Atlas and why they got into cash flow underwriting.
- The challenges of building a cash flow underwriting engine.
- What Income Navigator is and how it works.
- The different types of income they work with.
- Why they launched the Nova Credit back in March and why it is significant.
- The types of financial institutions they are focused on today.
- What is driving the new attention paid to alternative data.
- What they learned from their State of Alternative Data in Lending 2024 report.
- Some of the best practices in implementing cash flow underwriting.
- How lenders are using cash flow underwriting today.
- Why they decided to create the Cash Flow Underwriting Summit.
- What is on their road map for the next 12-18 months.
Read a transcription of our conversation below.
FINTECH ONE-ON-ONE PODCAST NO. 491 – MISHA ESIPOV
Peter Renton 00:01
Welcome to the Fintech One-on-One podcast. This is Peter Renton, co-founder of Fintech Nexus and now the CEO of the fintech consulting company Renton & Co. I’ve been doing this show since 2013, which makes this the longest running one-on-one interview show in all of fintech. Thank you so much for joining me on this journey. Now let’s get on with the show.
Today on the show, I’m delighted to welcome back Misha Esipov. He is the CEO and Co-Founder of Nova Credit. Now we had Misha on the show back in 2017, when his company was still very much a raw startup. Since then, they’ve gone on to be a really important part of the credit infrastructure in this country, and around the world for that matter. We go in depth about the different products, and also the new Nova Credit platform that sort of brings everything together. We talk in depth about cash flow underwriting, it’s such an important piece today. And it’s something that is very much a focus of Nova Credit as they have a summit coming up in New York, which we also talk about. Anyway, it was a fascinating discussion. Hope you enjoy the show.
Peter Renton 01:16
Welcome back to the podcast, Misha.
Misha Esipov 01:18
Good to be back. Seven years I think…
Peter Renton 01:21
It’s been a few years, yes, 2017. We talked a lot last time about the Credit Passport. And you were very focused on helping your rivals to the country bring their credit history into consideration for credit here, which I would have loved when I arrived here. So maybe we can start by saying when and why did you decide to move beyond that product?
Misha Esipov 01:47
Well, first of all, thanks for having me back on the show. I know it’s been a few years. And I still remember when you and I first spoke. A lot has changed in those seven years, right? Like we’ve been around for… we turned eight a few weeks ago, which is kind of crazy to say out loud. And going beyond the Credit P assport was always part of the vision. Breaking into the credit reporting space is a really hard puzzle to break into, right? You’ve got to build a differentiated product, you’ve got to build a data asset, you’ve got to become a CRA, you’ve got to figure out how to work with and partner with very large financial institutions, then you’ve got to figure out how to get a performance feedback loop to prove that your data insight actually works. So that whole cycle takes five to 10 years. And I can tell you a whole story about how we always knew we were going to build this big platform and do a bunch of other things. And, you know, Cash Flow Underwriting and Income Verification are now the two leading products that we’re pushing out there and seeing a tremendous amount of traction, it’s been a really exciting start to the year. But rather than tell you the happy story or the easy story, the reality is back in 2020, February 2020, we closed our series B and the timing, three weeks later, March 2020, Covid hits. And, you know, we almost went down to zero. And it was a really rough couple years. And we could spend a whole podcast talking about navigating that period of transition. But what it forced us to do is to accelerate our roadmap. And we invested a lot in product, started investing in Cash Flow Underwriting, income data, payroll data, bank data, different documentary types that we can handle. And in the last four years, these new product lines are growing at a great clip. And now we can come into the market and present a much broader offering: data for immigrants with a Credit Passport and a bunch of other data products like Cash Atlas and Income Navigator for other segments of the US population that are misunderstood.
Peter Renton 03:43
I’d love to get your sense when you’re when you’re meeting someone for the first time. How do you describe Nova Credit today?
Misha Esipov 03:51
Nova Credit is a credit infrastructure and analytics business that enables businesses like lenders, telecom providers, fintech companies, real estate companies, property managers, to underwrite anyone. And we allow them to underwrite anyone by harnessing a variety of new alternative credit data sources that are absent from the traditional credit bureaus. And I can go into a lot more depth around what those data sources are and what those products are. But in a nutshell, Nova Credit is a credit bureau, we are a CRA, a Credit Reporting Agency that plugs the gaps that exist in the traditional credit bureau system. And those gaps exist for about 100 million Americans who don’t have enough history to get approved.
Peter Renton 04:43
Okay, so I want to start off by diving into the Credit Passport. It is still the original product that you had. It’s been a few years now since the American Express deal was announced, right? So I’d love to kind of get a little bit of understanding of the history of that. How have you found that the relationships with, you know, a massive company like American Express? And when you signed them, you were just a start up. So how have you found that relationship, but more importantly, how has the data performed, like the people who have come into this country, got an American Express card through Nova Credit by bringing their history with them, what’s been the performance of those kinds of people?
Misha Esipov 05:27
We’re incredibly grateful to our partners at American Express for making a bet on us back in the day when they did and it was 2018-2019. So the product’s been out in the wild through an economic cycle now for the better part of a decade. And through that performance with partners like American Express, and many other leading banks, here in the US and around the world, we have more than enough evidence to empirically prove what our intuition told us, which is that immigrants are great borrowers. And you see that in performance that we, you know, we receive on a regular basis from our partners. And I’ll go a step further and to say that most newcomers actually outperform the average American, as maybe your intuition Peter would would tell you, as an Australian. So that’s really where we started. I mean, in those years, we’ve now deployed the Credit Passport around the world. And what I mean by that is both adding more data connections, so we have connections into about 4 billion consumer credit files from all around the world.
Peter Renton 06:34
That’s half the world.
Misha Esipov 06:36
Yeah, we’re about to cross half, yeah. For those that don’t know about the Credit Passport, basically, we plug into credit bureaus around the world, so bureaus in Mexico, Canada, India, UK, Brazil, Korea, Philippines, Nigeria, Ghana, and many more. And through that connectivity, anytime somebody moves from one country to another, we can use their home country history and get them approved in a new market. And so we started first by building out all this connectivity and bringing it into the United States. We’ve launched with some of the leading banks and card issuers here. And then over the last few years, we’ve also deployed that capability around the world. So you may have seen a headline from us with HSBC. So we’ve now deployed with them in the UK. You may have seen a headline with us with Scotia Bank last year where we deployed in Canada. And so the Credit Passport is now a real thing. It exists around the world, it’s supporting the biggest banks in the world and helping them better serve and win the only source of population growth in every major economy. So a lot of that pitch, you know, I’ll get off my excitement horse about the Credit Passport here in a second, but that picture is basically, if you look at US demographics, the US is going to grow by 40 million people. And 100% of that growth is coming from immigration.
Peter Renton 07:53
You see birth rates declining all around the world. We need immigrants and we need to have services for them, or you need to be able to help them bring their life to here. So I think it’s such important work. And I was glad to hear that immigrants perform as good or better than people who were born here. People come here to the United States because they want to, because they want to pursue an opportunity. You’re self-selecting almost into a positive kind of cohort by just the mere fact that they’re immigrants, I think so. Let’s move on to to Cash Atlas, and when did this come to be? We’ve been talking about Cash Flow Underwriting for a while now. So tell us about Cash Atlas.
Misha Esipov 07:53
Yeah, so Cash Atlas, we started building back in 2020. I mean, I’ll take you through a little bit of the history here. Covid hits, the economy goes into a state of freeze. And if you go and you know, what we did is we went in, I called a lot of our existing customers and prospective customers, and I said, hey, we’re great team, we’re a CRA. We know how to build data connections, we know how to do analytics, we know a thing or two about credit risk. What do you need help with? And the problem du jour then was this question of how do I know whether my applicants are still employed and whether they have an ability to pay their debt? And that basically is the question that Cash Flow has the ability to answer. Is the customer still receiving an income? Do they have the cash to service their debt and their obligations? And so we started investing very heavily into bank data connectivity. Our approach has been very different than that in the rest of the market, but to to boil it all down, Cash Atlas is cash flow-based underwriting using bank transaction data across all of the major bank aggregators to allow risk teams and businesses to make more informed and fair risk decisions using bank data.
Peter Renton 09:56
Okay, so you’re connecting to banks through a variety of aggregators?
Misha Esipov 10:01
That’s right.
Peter Renton 10:02
So not just Plaid, but others that are in the market as well.
Misha Esipov 10:05
Yeah we work with many of the leading bank aggregators, we’ve built our features and our attributes and our scores to be compatible irrespective of where the bank data comes from. And we’re all in on cash flow underwriting. You may have seen, we’re hosting the industry’s first Cash Flow Underwriting Summit, which will be in New York in September. And the reason we’re so excited about it is we think that cash flow data has the potential to be as good or better than credit bureau data. Like if we had to rewire the credit bureau system today, there is no doubt that the industry would like that information to be built on top of cash flow data. And when you look at that data, what you see is you see income, you see expenses, you see assets, you see whether someone overdrafts. And the combination of deeper data, more current and uptime data, it’s a real time snapshot, as opposed to bureau data, which is lagging. And then finally, higher coverage, like far more Americans have a bank account than those that have a credit file. That combination of factors makes this information incredibly powerful from a risk perspective.
Peter Renton 11:12
I am fully on the Cash Flow Underwriting bandwagon. Have been since really, it came out. I think it’s a shame that not more lenders are using it today. I think soon everyone’s going to use it, I’m convinced and I’m sure you are too.
Misha Esipov 11:27
We think so too.
Peter Renton 11:28
The fact is, the cash flow data is not easy to work with maybe just touch on that for a little bit. Because you know, you’re a CRA, which means you can really synthesize this data, analyze it and provide insights back to the lender that they can use in underwriting. But I mean, tell us a little bit about that process because every bank probably has a slightly different format. And I just looked through my bank statements, and it’s just, you know, it’s a myriad of different types of descriptions and what have you. How have you been able to bring that intelligently to your lenders?
Misha Esipov 12:00
There are a lot of challenges with building out an enduring Cash Flow Underwriting engine, The premise is pretty clear, and becoming increasingly accepted. In you know, I’ll say I’ll call it “mainstream credit risk land” that cash flow data can drive a tremendous amount of lift in incremental approval swap-ins, it can drive value in terms of line assignment, better pricing, CLI, CLD, it can drive account management use cases, it can drive cross sell use cases, there’s a tremendous amount of potential for what cash flow data or bank data can drive. But it’s blocked by a series of challenges. And many of those challenges are very difficult for banks to figure out how to navigate on their own. The first of those challenges is that this data tends to be permissioned, righrt? You have to credential into this data. And so understanding that tension between user experience and credit risk insight is one that very few teams in the world have learned how to do for the biggest banks. And it’s something that you know, it’s honestly, it’s the same challenge with the Credit Passport, because the Credit Passport data is also permissioned in tapping into this data from around the world. So there’s issues in challenges with consumer experiences, challenges in coverage, and latency and uptime and data standardization and building the analytical attributes, building the credit scoring, building the compliance, and I think our our view is that the same way that every major bank and lender works with multiple bureaus. Our view is that every lender will work with multiple aggregators. In the long run. If we just fast forward in how we think about this, and the impact of that is that in order to build and maintain your feature set on one and then other platforms, that’s a tremendous amount of work and effort, and we make that a lot easier for for our partners. And so that’s really the strategy and the approach behind it. We’ve been betting a lot on this as a strategy and had some really tremendous results in the last few quarters.
Peter Renton 14:02
Okay, so let’s move on then to Income Navigator, because that’s another important piece, income verification. It’s a complicated thing. Now, we’re a long way removed from the time when everyone just had one job. Tell us a little bit about how and why you developed Income Navigator.
Misha Esipov 14:20
Yeah, I mean, the the income challenge is actually how we made our way to Cash Flow Underwriting, right?
Peter Renton 14:26
I’m wondering which one came first?
Misha Esipov 14:27
Well, there used to be one product and then we kind of broke them out because they are different at the end of the day. It took us a little too long to figure out. But Income Navigator solves the question of how do you verify in an automated manner, whether an applicant has generated income and what that income is. And we do that through a multi-step process, multi-step workflow that’s been optimized across millions of income verifications at this point across many different product lines. And we’ve used a combination of payroll data, bank data, various documentary types and a variety of other capabilities to optimize that workflow and experience without compromising the data quality. And so, you know, we first launched Income Navigator with SoFi, back in 2020. So it’s been out in the market now for three, four years, and a really powerful tool to drive automation and help improve the customer journey with getting folks approved, and their income verified, and complement the gaps that exist for products like the work number and some of the others out there.
Peter Renton 14:57
You’re not doing this, like the work number, right? Where you’re creating a centralized database with all this information? How are you implementing it? You’re doing this in real time when someone’s requesting this and how does it work?
Misha Esipov 15:48
Yep, that’s exactly right. So it works the same way as all of our products do. So that the way to think about Nova Credit, is that we’ve got the infrastructure to tap into new data sources, we’ve got the analytics to standardize those data sources, and we have the compliance to ensure that that data is used compliantly as a CRA. And so every one of our products is the same concept where it’s, you know, it’s a workflow that we power that we embed into our partners. And we can configure that workflow to do anything a bank needs around their alternative credit data use. So we can pull in data from around the world, we can pull in bank data, we can pull in payroll data, we can handle different documentary types. And so what Income Navigator does is it pulls in on a subset of those data capabilities, it standardizes them and it delivers that information compliantly back to the business.
Peter Renton 16:37
So does it also work with 1099 gig worker type things? Are you are you able to pull in some of the major players there?
Misha Esipov 16:45
Yep, definitely. So we’re pulling in that data across different data categories. So payroll systems, HRIS, systems, bank data. So we’ve got, you know, a calibrated workflow that we go through to be able to automatically verify income on about 98-99% of Americans.
Peter Renton 17:05
Okay, so I want to go back to the the big announcement you made in March. You launched the Nova Credit Platform. So maybe explain what that is. And what’s the significance?
Misha Esipov 17:16
Yeah, the Platform is a culmination of eight years of data infrastructure, analytics, and compliance investment. So all of our features, all of our products, all of our connections are made available through one offering. And if you kind of like maybe to set like a broader, like, problem statement out there, for the listeners, and for the broader fintech community: if you look at US consumer credit data, there are still 100 million Americans who struggle with basic financial access, and you can break that number down, and you can look at those that are, you know, subprime, near prime, thin file, no file new to country, a bunch of these, like smaller categories. And if you ask the Bureau why is it that there’s still 100 million Americans who struggle with access, many would say, it’s because there’s not enough data out there. Just not enough data on who these customers are. And it’s really, that’s why we’re struggling to bring them in. And so they’re investing some, you know, they’re building some great products to help bring more data into the Bureau. But our view is quite different. Our view is actually there’s an abundance of data out there. And the missing piece is the ability to instantly tap into that data, bring it in, refine it, make it usable, make it compliant, and to deliver that. And that’s precisely what we’ve done with the Nova Credit Platform. And so the Nova Credit platform is connectivity into bank data, payroll data, Bureau data, global Bureau data, different documentary types, and a standardized ability to access that information and in real time use it to approve customers that are traditionally misunderstood.
Peter Renton 18:55
Who is primarily using Nova Credit today? I mean, are you across the board, like, obviously, you talked about American Express and SoFi. Are you just as focused on the banking space as you are on the fintech space? What about the types of lenders that you’re working?
Misha Esipov 19:11
We’re primarily focused on the larger banks. We definitely have sizable non-bank lenders and fintechs as partners, but we’ve primarily focused our efforts on the larger financial institutions. And the variety of reasons for why that is, part of it is our history, part of it is our strategy. But you know, at the end of the day, the big banks still dominate consumer lending. And so the ability for us to have the most impact requires us to find a way to support those big financial institutions and innovating the kind of data they can use to approve more people.
Peter Renton 19:45
So talking to those big banks, I’m curious, and you’ve been working with some of them for many years now, is the recognition of the importance of what you guys are doing and maybe just the alternative data in general, is there a greater recognition of its importance today? And how are those conversations going?
Misha Esipov 20:05
I think the expectation of a risk officer in the last two years has changed. If you went and did these surveys or talked to a bunch of risk officers and bank leaders, two years ago, there was only one priority on their mind. And that priority was recession proofing. And so for the last 18 months of the last two years, they were focused on recession proofing, recession proofing, recession proofing.
Peter Renton 20:32
And it never came. The recession never came.
Misha Esipov 20:34
It never came. It may still come, no one has a crystal ball. But you can only recession proof for so long before either you get bored or the expectations change. And in the last year, partly triggered by the proposed rule 1033, partly driven driven by us and players like us who are helping drive the industry forward to adopt some of these new capabilities, there is a heightened level of expectation that as a risk officer, you need to be investing in new data categories. And on top of that, if you take a very critical look at what’s changed in the traditional credit bureau data environment, there have been a few secular shifts that have happened that have made the credit bureau data far murkier, far more difficult to understand, than ever before. And I’ll call out a few of those. And I think you’ve talked a lot about the BNPL data that’s out of the Bureau and all of that shadow banking data, there is data around government stimulus, that is inflated, there’s all of this, like credit builder stuff, that’s inflating credit scores. And you know, the leading indicators of the impact of a lot of those credit builder products is that they’re actually creating adverse selection, and over time, not actually great, contributed to these scores. And then you have things like soft inquiries, where you know, hard inquiry data is now gone. and so the data environment of the traditional Bureau has never been more difficult to use. And so the industry is now finding that the scores just aren’t as predictive as they used to be. And so there’s this shift happening, where more and more lenders are investing in alternative data capabilities to be able to continue to grow responsibly.
Peter Renton 20:34
Okay, you put this report out earlier this year, The State of Alternative Data in Lending 2024. Can you just hit on some of the highlights of what you learned from that report?
Misha Esipov 22:42
Yeah, I mean, a few of the highlights I mean, about a third of lenders don’t believe that credit scores accurately represented credit worthiness. Let’s just pause on that one for a second. A third of risk professionals no longer believe that credit scores are an accurate representation of credit worthiness like that, that one certainly caught me by surprise, that number was about 15%, or 16%. I think it was 15% or 16% two years ago. So that’s nearly doubled. And that’s driven by some of these factors that I just walked through. Less than half of the environment is using any form of alternative data, but that number is increasing quite quickly in the last few years. And so that kind of speaks to the expectation that as a risk officer you need to be using this information. And almost all, I think the number was 93%, of lenders believe that this alternative data ultimately has a positive impact on their KPIs. But it works.
Peter Renton 23:37
Right.
Misha Esipov 23:38
It works. And so we’re in this adoption cycle right now, I’d say still relatively in the sort of early mid innings of it. But with every passing quarter, we’re seeing a heightened level of interest, appetite, deployment results, and how to use this information. And that’s one of the things that makes this environment such an exciting one to get to continue to build in.
Peter Renton 24:02
If you want to implement, you’ve never used Cash Flow Underwriting, but you want to bring it in or you want to know more about it. What are some best practices for implementing Cash Flow Underwriting into your underwriting process?
Misha Esipov 24:16
Well, the most important thing you can do is to get started. The wave is here, it’s picking up the regulatory environment has largely cleared. And this information has been sufficiently tested and proven over the years to be able to confidently separate risk. And I think what the conceptual problem that most risk officers will struggle with is this concept of perfection being the enemy of progress. And what I mean by that is in the credit bureau environment, most lenders are accustomed to having access to near perfect information around how this information works. In the open banking environment, it’s a different construct, because you have to go out and fetch this data. And what many risk teams get stuck in is this like analysis paralysis of trying to find the perfect piece of analysis to hang their hat on. And you can spend years working on that. Those years come at the expense of making real time progress and driving any of your KPIs forward. And so part of our superpower is really to help partners through that process, and ensure that even if you take a conservative stance, you don’t allow that conservative stance to prevent you from taking a step forward.
Peter Renton 25:38
So the lenders that are using it today, is that mostly on a second look basis for people that are just marginally declined, and then they go back and check? Is that the primary use case?
Misha Esipov 25:49
That’s one of the key use cases. The other one that we’ve seen had a lot of success is credit line increases or pricing improvements. So giving applicants the ability to improve their line assignment by opting into sharing more information.
Peter Renton 26:04
Let’s talk about your Cash Flow Underwriting Summit. You touched on it earlier, but what was the thinking behind that? And what are you trying to achieve here?
Misha Esipov 26:14
If you believe that the CFPB and the regulator wants this, which, you know, they’ve been pretty clear about their belief in Cash Flow Underwriting as an important…
Peter Renton 26:25
Explicit. They’ve been explicit about them.
Misha Esipov 26:28
And you believe that there’s business value, then there’s got to be a way to accelerate the adoption of cash flow underwriting. And that’s really what we’re after. We’re here to help share what we’ve learned in our many years of supporting some of the largest banks and fintechs out there with using this kind of information to create that space, bringing a combination of banking executives, fintech executives, regulators, we’ve got the CFPB coming, and will be speaking at the Cash Flow Underwriting Summit. It’s in New York taking place on September, I believe, 12th. Great time to be in New York, right after the summer. And it’s also just, you know, an opportunity to hear about the real world use cases of how this information has been implemented, impacted, thriving, in a way to help advance the field. I think what you know, every business out there has an opportunity to not only grow responsibly, but also do a tremendous amount of good in helping segments that are misunderstood by the traditional bureaus into the financial system more fairly, and in doing so, improve their brands, unlock new marketing capabilities, unlock new product features, and hearing that perspective, will, in our view, advance the field by more than us doing these like little one off meetings, or speaking at summits. And so we thought, you know what, let’s just go all in on this and bring, you know, leaders in the field together and see if we can help pick things up a little faster.
Peter Renton 28:02
Last question, then, what’s next for you guys? What’s on your roadmap the next 12 to 18 months?
Misha Esipov 28:08
We just posted a Head of Product. So I’ll put that out there. Anyone who’s been deep in credit infrastructure and analytics, and ideally, someone who’s seen how to scale out an organization on the product, data science, and other parts side. So I’ll put that out there. I mean, we’re growing. It’s been honestly, Peter, as someone who’s been building this business for a long time now and like OG fintech at this point, it’s been refreshing the last few quarters, as the market has turned. I think banks are spending on technology again, they’re investing in new capabilities. And you know, we’re doing the best we can to keep up with demand. It’s a privileged problem when that is the issue du jour and we’re having fun, we’re continuing to invest in new product capabilities, invest in new verticals. And we’ll have a few more exciting announcements to come ahead of our Summit and end of year next Summit.
Peter Renton 29:04
Well, we’ll have to leave it there, Misha. Thank you very much for coming on the show. Great to chat with you as always, and best of luck.
Misha Esipov 29:12
Thank you. Thanks for having me on.
Peter Renton 29:15
Well, I hope you enjoyed the show. Thank you so much for listening. Please go ahead and give the show a review on the podcast platform of your choice and go tell your friends and colleagues about it. Anyway, on that note, I will sign off. I very much appreciate you listening, and I’ll catch you next time. Bye.