CEO of Nova Credit Talks Financial Inclusion and the Future of Credit Data

Rich Alterman  00:04

You're syncing up and tuning in to the Lending Link Podcast powered by GDS Link, where the modern-day lender can dive deeper into the future of data decisioning and Credit Risk Solutions. Welcome to the show, everyone. I'm your host, Rich Alterman, and today we are syncing up with Misha Esipov. Misha is a co-founder and CEO of Nova credit, which was launched in 2016 a leading credit infrastructure and analytics company helping lending institutions to grow responsibly by streamlining onboarding, verification and underwriting processes of credit data. In 2022 Misha was listed as one of 23 people who will matter in banking in 2023 by the American Banker. The company's differentiated data sources and proprietary analytics are used by leading organizations like American Express, horizon, HSBC, Sofi and Yardy, to name but a few. Nova credit is backed by investors including Kleiner Perkins, general catalyst Index Ventures and Kanopy, as well as executives from Goldman Sachs, JP Morgan and Citi, before founding Nova credit, Misha was a private equity investor at Apollo Global Management, a 230, $2 billion global alternative asset manager company. Misha started his career at Goldman Sachs, where he helped execute more than ten billion in corporate financing, mergers and acquisitions. Misha holds a BS in mathematics and finance from New York University and an MBA from the Stanford Graduate School of Business. In this episode, Misha and I will be discussing the background of Nova credit and how it is helping address financial inclusion for both immigrants and thin no credit individuals and so much more. But before we dive into the interview, please head over to our LinkedIn and Twitter pages at GDS Link. That's GDS Link and hit those like and follow buttons if you have not done so already. Please subscribe to our podcast on Apple podcast Spotify, or wherever you prefer to listen to your podcast. All right now, let's get synced with GDS Link. Welcome Misha and happy Friday. Hope you've had a great week. Where are you joining us from today?

Misha Esipov  02:14

I am in our New York office.

Rich Alterman  02:16

Good and once again, thank you for spending time with me this morning to share more about Nova credit and how it is helping consumers in the lending industry. But before we talk, let's get a bit personal. I understand that you're a gymnast and wrestler in your early days, and that you can still entertain your friends and coworkers with the occasional backflip and walking on with your hands. How do you feel the disciplines you have had to develop to be successful in sports have helped you in your career?

Misha Esipov  02:39

I don't think I've ever been asked this question, but it's definitely something I think about from time to time, entrepreneurship and building a company requires a tremendous amount of pain tolerance, and just like suffering through that, and few physical sports disciplines require more suffering than wrestling. And so I think the whether the both of the physical requirements of the sport, the mental requirements of the sport, cutting weight over the course of, you know, many, many months, having such a high pain tolerance, I think, has certainly contributed to my ability to persevere and persist through, you know, not, not a cleanup into the right story. And so, I attribute a lot of that to, you know, the discipline of growing up and doing those sports.

Rich Alterman  03:31

Oh, good. Well, thanks for sharing that. So, let's get down to business. I recall correctly, I think I first met you and your co-founder, Nicky Goulimis, in around 2015 when you were first exploring the idea of starting Nova credit, please share how you and Nicky came together. And you know what was the catalyst for starting Nova credit? That is, you know, what was the problem you and Nicky were trying to solve and why?

Misha Esipov  03:51

Yeah, so we were grad students at Stanford, and we're just generally interested in this question of, how do students make financial decisions, and we started doing a ton of user research, user interviews, and asking over 100 students, do you have a credit card? How'd you get that credit card? How'd you make that decision? Do you have a student loan? How'd you get that student loan? How'd you decide that was the right student loan for you? And a bunch of other kind of personal finance questions, and through that user research, we uncovered a problem statement. And that problem statement was that half of the people we were speaking with just so happened to be international students, and 100% of that half would tell you some version of the same problem that we've now solved, and the story went something like, I can't get a credit card, I can't get an auto loan, I can't get a student loan. I have to go beg my classmate to put me on their cell phone plan. I have to go ask my you know, my third uncle to cosign an apartment lease for me, and it was indicative of a systemic problem faced. By half of the graduate student population of just about every graduate school in the country, and that is faced by all the international students. And as we started to peel back the onion, we realized that this was a problem not only faced by international students, but a problem also faced by millions of people who moved to the US every year. And if you dig in deeper, what you'll realize is that the root of the problem is really an issue of a credit bureau system where millions of people move to the states. They arrive credit invisible. There's no information about who they are, and so they struggle and spend years building credit history. And rather than making that the status quo, we thought there must be a better a better way. And so, over the course of the last, you know, eight years, I'm sure we'll get into it. Nova credit has emerged, as some would say, the fourth credit bureau. I don't like to be fourth, fourth in anything. So, you know, one day will be third and second, and who knows, from there, maybe first. But we do a lot of different things. We help immigrants get access to credit. We help Americans get access to credit. We help people get into housing. We help people do get approved for credit cards and auto loans and student loans and mortgages and a bunch more. So that's a little bit on the high-level arc, and I'm sure we'll get into the details here.

Rich Alterman  06:14

Well, great. So yeah, so once again, the initial goal is to help immigrants to the US secure a quicker path to financial inclusion by helping them more seamlessly share their credit files with us lenders. And obviously that's called your credit passport product. So, with almost, or actually with eight years under your belt, let's spend some time getting caught up. So, tell us what's new,

Misha Esipov  06:36

yeah, so the big thing we announced this year is the Nova credit platform, right? And what the Nova credit platform is, is, is an assembly of all of the products and services that we've created over the last eight years into one, one holistic offering. And maybe I'll, I'll start first by talking a little bit about how the problem statement has broadened, and how the Nova credit platform helps solve some of these really tricky industry problems that have been around for far too long. So if you look at our US credit system, there is this catch 22 and a lot's been said and written about it, where you need to have access to credit, where you can only get access to credit if you have credit history, and you can only build credit history if you've had access to credit. And so, it sort of creates this system of haves, haves and have nots, right? And for in that system, that is terrible when it comes to people who are new to that system, whether that be young adults, whether that be immigrants, whether that be other pockets of the US population. And so, what we announced with the credit passport is a series of tools and integrations that really plug those gaps that exist in the credit bureau system. And if you ask some of the credit bureaus, how is it possible? It's 2024 there's still 100 million Americans who are thin, file, no, hit subprime and struggle with basic access. What they'll say is there's just like, there's just like there's just not enough data in the credit bureau, we got to find a way to get more data in the credit bureau. And I actually think that's the wrong way to think about this problem. I think the right way to think about this problem is there's an abundance of data out there. There's data in your bank account, there's data in your payroll system, there's data in global credit bureaus. There's data and documents that you have the ability to provide. And what the Nova credit platform does is we allow our partners, partners like American Express and HSBC and SoFi and many banks here in the States and around the world to tap into these new data sources and instantly use those to help create a clearer picture about who a given applicant is, and in doing so, create a more fair and inclusive financial system.

Rich Alterman  08:44

Okay, great. You know, let's break the Nova credit platform and its core three products down. Let's start with sharing how credit passport actually works and the type of reach you have across the globe today.

Misha Esipov  08:56

Yeah. So, credit passports are arguably our most mature product that exists here in the US, that exists around the world. The way the credit passport works is we got on a plane, flew all the way around the world, met with credit bureaus and regulators in every major market that contributes to us, immigration. So went to India, Mexico, Canada, the UK, you know, Philippines, Brazil, Korea, and we built data partnerships with all of the leading bureaus in all of these markets and many more. We integrated into those credit bureaus. We standardized the data that we have the ability to extract, and we've effectively created an aggregation layer on top of the world's credit system. And fast forward many years now, we have connectivity into more credit bureau data than any company in the world. To college. We have access to data in, you know, over 20 countries we have access to data on about 4 billion. Consumers. So, we have access to about half of the world's adult population in terms of their history, and through that connectivity, we have the ability to serve about 70% of the annual inflows into the US. And so, we've gotten to this critical mass of connectivity in helping people who are new to the US to not have to start over, to being able to use the history they've built on themselves in their home country. And, you know, getting a leg up and fast tracking their ability to integrate into the US and the credit passport exists here. So, we thought you could think of it as like a marketplace. On one side, we have access to bureaus, and, you know, 20 plus countries on the other side, we distribute this data into several markets. So, we started with distributing the connectivity into the US, where we've where we are a credit reporting agency. And we also now distribute into other markets where we're licensed as a credit bureau, like Canada and the UK. We also distribute into Singapore and the UAE. So, if any of the listeners I heard, you had your listeners in you know, over 50 countries, if any of those listeners move to any of these markets, they have the ability to use their history they built in their home country in a new market through us. Or if you are rich, you've had it here in America. You want to move to Canada; you want to move to the UK. We can help you use your US history and get approved for financial products there.

Rich Alterman  11:23

Great. Well, I don't think I'm quite there yet, but we'll see what happens. So, you know, you mentioned dealing with all these different countries and meeting with the bureaus. I suspect one of the big challenges that you face is navigating all the different rules and regulations governing the use of credit bureaus in each jurisdiction, such as GDPR, can you share, you know, what's the process you develop to, you know, properly address these complexities that that presents.

Misha Esipov  11:47

So, every market has its own rules and regs. Right here in the US, we have the FCRA. We have our fair lending laws and ECOA. You know, Canada has its own rules. Europe has its own rules. Every country within Europe has its own rules, then there's extra territorial rules like GDPR and other four-letter words that regulators love. And no one has created a single global framework to talk about consumer credit data or to talk about and regulate global data privacy, right? Every country has its own, dare I say, self-serving rules that protect its citizens and that created this sort of regulatory puzzle that has prevented the problems of cross-borders, credit history, mobility from ever being historically solved. And our approach, from the very onsite onset in one of the aha moments in the business was realizing that regulators believe that consumers own their data, and if you believe that a consumer owns their data, and you believe that a consumer has a right to their data, then if that consumer is able to prove that they are, in fact, who they say they are, that consumer has The right to have their data move with them as they move from one country to another, and that was really the tip of the spear in our regulatory argument, and going to these bureaus around the around the world, and setting up these partnerships and meeting with regulators and ultimately establishing, for the very first time, the ability to move this Country, move this information from one country to another compliantly, and then once the information is in the destination market, let's say the United States, we have to abide by the US law here, and the US law here makes clear, well, not clear, but makes relatively clear that you should be a credit reporting agency, and we Were one of, if not the first venture backed business to step into the shoes of actually operationalizing a set of policies and procedures to be a credit reporting agency. And so, we took on that challenge when we were still a sub 10 person team back in 2016 and over the course of our history, we've continued to be a CRA here, and that's allowed us to win and serve, you know, the biggest banks in the country.

Rich Alterman  14:05

And certainly we're, you know, waiting to see where rule 1033 of the Consumer Financial Protection Act ends up. Sure, you guys participated in some of the Q and A that the CFPB had put out. So, one of the things that companies certainly still rely on our credit scores. And you know, out of curiosity, do most of the countries that you've worked with also offer some type of generic credit score, similar to a FICO and advantage,

Misha Esipov  14:30

I'll take the question one click higher, which is to color a little bit about the not only the scoring, but the global credit bureau landscape, every major economy with I'll say one exception has a credit bureau. The one exception, and we can, we can giggle about it, is France. France does not have a credit bureau. They have a government owned registry, negative registry. But every other major economy has one or more. For credit bureaus, and more typically than not, multiple credit bureaus. And so, this data exists around the world, and this data does the same thing that it does here in the States, which it supports the safety and soundness of the consumer lending market, and in each of those markets, there are then nuances to what is captured in this data. And most important nuance is whether the data is positive or negative. Reporting. In the US, we follow a positive reporting environment where both the good and the bad are reported to the bureaus. And some countries, like in in Brazil, for example, only the bad is reported. So good customer information, like I did pay on time, would be good information that doesn't get reported. And then comes your question on scores, which is, how do you then make sense of, you know, this data that these bureaus capture, and basically every Bureau around the world has one or more credit scores that they build. Some of them build it in house. Some of them partner with scoring companies like Fico. And then once that score has been established, we partner with those bureaus to develop a scoring translation methodology that will allow for that score to be used in the destination market.

Rich Alterman  16:06

So, do you align? Do you work to align those scores, similar to a FICO advantage? You know, 300 to 850 as a standard range?

Misha Esipov  16:14

Yeah, we map our scores into the destination markets, right? Scoring standards. And so, 300 to 850 means something here, but in the UK, that doesn't mean anything. And so, every country has its own standards for core ranges that you know the local risk officers are accustomed to understanding.

Rich Alterman  16:36

So, in the US, you know most, maybe most of our Hopefully, most of our listeners may be familiar with the Metro two format, which is what lenders use to report into Equifax, Experian and TransUnion. But you know, as we know, each of those three bureaus outputs the data in a slightly different format than what comes into them to be unique from their competitors. Did you adopt any particular output method to more align with any one of the bureaus. Or did you go about developing your own?

Misha Esipov  17:05

We've developed our own proprietary score mapping methodology, and part of that is because the underlying data definitions around the world are different. There are nuances to credit bureau information all around the world, like one of my favorite examples is in India, the most common trade line is one that American bureaus have never heard of, and that is the presence of a gold loan. And so there's nuances in what this data looks like, how it's defined, and we spend a lot of time and rigor going on site and understanding these data definitions and ensuring that we can ultimately represent and develop a product that, again, the most reputable financial institutions in the world are comfortable relying on and making decisions on.

Rich Alterman  17:55

yeah, it's interesting. When I was at Teletrac, which was the first ever payday loan credit bureau, we were working in the UK and working with one of the main bureaus there to ingest payday loan data. And they, they really, once again, that, in itself, was a challenge. You know, how do we take a two-week product or a monthly product, and roll that into a traditional credit file? So, it's interesting that, you know, the process can get pretty complex. So, I know that America Express was your first lender to incorporate credit passport into its underwriting process for immigrants into the US. So maybe you could share some stats on what's the general impact that it's had on their lending business, and how many more applicants have they been able to approve? Maybe talk about it generically, if you can talk specifically to America Express.

Misha Esipov  18:39

yeah. So, we launched a partnership with American Express 2019, so, I mean, it's been five years, six years now, time flies when you're sometimes having fun, I guess. And that partnership made American Express wasn't our first customer. They were certainly our first major customer. And we enable American Express to instantly digitally approve applicants for their consumer cards. 100% of their US consumer cards using cross border credit bureau data. So if you move from London to New York and apply for an American Express, American Express relies on Nova credit to go and fetch the data from the UK, bring it into the US, standardize it, turn it into a compliant us report and deliver that to AmEx, so that they can take someone who's otherwise credit invisible and get them from a no to possibly a yes. And so, you know, they helped pioneer that, at least among the big the big banks and issuers. And over the course of four or five years, we've now seen, you know, real volumes seasoned credit performance. And I think the punchline, and we have some public case studies on this, is that the credit passport does a phenomenal job of separating risk, and that immigrants are new people that are new to country are really good credits the credit performance of these. Segments are as good or better than, you know, the overall US, US average. And in addition, the thickness of the file, meaning how well established is someone's experience with credit prior to moving to the US is actually quite thick. On average, they have, you know, about 10 trades. The average age of their trades is about 10 years number of open trades on average, about five. They do utilize their credit and the index delinquency is meaningfully better than the average US population does.

Rich Alterman  20:32

Most of the other countries that you work with also have public record data, like bankruptcy, liens, judgments and things like that many do, okay, okay, cool. I know we talked about, you know, we started with you guys started to support immigrants into the US. You've now mentioned that, obviously you're doing a lot of work where people may be moving into other countries, let's say India. So, you know, maybe you could share some of the successes you're having for immigrants going into other countries and talk a little more about your partnership with HSBC.

Misha Esipov  21:04

So, we started investing in internationalizing the product in 2020, that started, you know, with setting up our legal and regulatory structure in many of these markets where formal licensing is required. So, as I think I shared earlier, we are licensed credit reporting agency, you know, with the FCA in the UK, we're licensed in every province in Canada, and a few other markets that we're that we're working on. And our first major international partner was HSBC, and so we signed, and this is all in the public domain. We signed a global partnership with HSBC back in I want to say 2021 I believe where we enable HSBC, we are basically the backbone of HSBC ability to underwrite new to country. And so, we first launched that in Singapore. So, you know, people from around the world that we have connectivity into moving into Singapore, can use that to improve their eligibility for products from HSBC and Singapore. Then we've launched that in the UK, and that's what, what's public right now. And you know, we're incredibly excited about that relationship. And it's continued. It's continued growth across product lines and around the world, but certainly still in its early endings of deployment, but seeing some real scale in some of those markets beyond HSBC, maybe I'll put a quick plug in for Canada, where I'm spending a lot of time in Toronto these days, and we were public about having launched a partnership with Scotiabank last year. They were the first, you know, call it top five Canadian bank to onboard onto the credit passport and to the Nova credit platform. And through that, are able to improve their products, their services, their onboarding experiences, their line of time, a bunch of different things that the credit passport has been able to help others. Others do you know Scotia is an early adopter for us in Canada, and being able to really leverage what some of these, these data capabilities, can do? I love Canada right now. Canada is just it's moving fast. The adoption cycle is much faster than in the US. And I think it speaks to just how acute of a pain point this is in Canada, right, as well as how competitive and focused the Canadian banks are on winning new to Canada. And maybe I'll put a few numbers on it around it for you and for the listeners here. So, in Canada, you got a population of about 40 million people. And the next 20 to 30 years, Canada is expected to add about 12 or so million to its population, to grow to about 52 100% of that growth is coming from immigration. 100% of that growth. And so if you're a bank and you want to grow, there is no way to grow without a dedicated, data driven strategy for how to attract and retain the new to country segment, the parallels and so in Canada, every major bank has a named executive who's expect, who's responsible for, you know, improving and developing their new to Canada strategy for how To how to create and improve their product offering for those, for people who are, who are new to the country, in the US, the numbers are even bigger in the US, where, you know, population just over 300 we're going to grow by about 50 million people in the next 20 to 30 years. 100% of our growth here comes from immigration. The same it's the same story. The absolute number of immigrants that are coming to the states are, you know, three to four times the size of Canada. But our banking sector is much less concentrated. And, you know, some would argue, not as competitive as the Canadian Dare I say oligopolies, like there are really five, six. Seven big banks in Canada, US, we have, you know, 1000s. And as a result, the level of focus in the US on this segment is still in the early endings, but it's starting to change. And we're starting to see more banks invest in new to new to the US teams, newcomer teams, multicultural banking teams. And really excited to continue to see that trend play out.

Rich Alterman  25:20

So, you're working with any alternative lenders up in Canada, like someone like a go easy?

Misha Esipov  25:26

Yes, we, you may have seen in the headlines last, end of last year, we announced a partnership with Go Easy, where they're the first, you know, non-bank lender to leverage the credit passport, to improve their offering for new to Canada, right?

Rich Alterman  25:40

Well, great company to one of our clients.

Misha Esipov  25:43

So, we're huge fans of the team there. I mean, Jason, Jason and Jason have done a phenomenal job.

Rich Alterman  25:48

Okay, so thanks for the rundown on credit passport, which is, you know, certainly one of the keys, key assets within the Nova credit platform. So, let's, let's now talk a little bit about your cash Atlas and associated Nova score cash flow and income navigator. So why don't you please share more about these offerings and how they complement credit passports?

Misha Esipov  26:08

Yeah, so this, this concept of cash flow underwriting, is not a novel concept, right? But it's one that's been talked about for decades, and unfortunately, very poorly executed by banks and the various, you know, bank data aggregators and providers, without getting into names. And over the course of the last few years, maybe I'll actually go all the way back to 2020, when covid first came through, and you saw, you know, this shock to our labor market, every lender was worried about one in the same problem, which is, I don't know whether my applicants have a job and whether they're generating an income. And there was this heightened level of focus and attention on ability to pay, right? And it was from following that thread that we ultimately landed on building a product that we call cash Atlas, which is cash flow underwriting as a service, and so we have the ability to plug into bank transaction data, whether it's within the four walls of a financial institution, whether it's within the four walls of a different financial institution, and to use that information to help make more fair and informed lending decisions, and this product has been shown and proven to be incredibly additive in terms of bringing orthogonal credit bureau insight to many segments that the traditional credit bureaus don't understand. And so, I'll pick on roughly the 30 to 50 million thin files, that thin file no hits here in the US, where the bureaus just don't really know who these customers are and how good or bad of borrowers they are. And so if you're a lender, most lenders will default to turning them down because they're just not sure, especially in you know this like heightened anxiety, prone macroeconomic state that we've been in for the last for the last two years, or, you know, most lenders have significantly contracted their Buy Box. And through cash Atlas, we're able to understand these otherwise invisible or misunderstood, I think, is a better term, misunderstood segments, with far greater clarity. And the way that we do that is we, you know, with their approval, we look into their bank account, and in that bank account, we can find a treasure trove of really valuable information. We can see someone's direct deposit. We can see other income streams. We can see expenses. We can see their assets. We can see whether they've over drafted. We can see trends in that information. We can see the amount of recurring expenses they have. There's a, there's just a treasure trove of information that, if you had to, you know that that's so that's so valuable that we're able to boost approval rates without compromising, you know, risk, quality and without increasing bad rates for you know, many of the, you know, largest banks and partners now here in the States and hopefully soon, around the world, and that capability is creating on ramps into the financial system and breaking through this catch 22 that has plagued the credit bureaus for so long, and it's sort of, it's an obvious thing to work on and to build. It's a very hard problem to crack, and it's hard because there are, are a lot of nuances across having the data coverage, having, you know, having a seamless user experience, the extent you're working with third party, being able to pull this data quickly, having reliable, high uptime, being able to use information compliantly as a bureau, having the right features and analytics, and ultimately, you know, provide. Getting that FCRA level solution, and so it's a big bet for us. We were four, almost five years into investing in it, very excited about the traction and the continued, continued momentum. And, you know, I'm an entrepreneur, and you know, looking forward, my expectation is that every financial, every consumer credit decision, you know, I don't know if the number is five years or 15 years forward, will use some component of cash flow data. And I think that's the direction we're going. And we're betting the house that, you know, we are certainly a leader in the race, but that we're ultimately going to help continue to drive the industry forward.

Rich Alterman  30:42

Certainly forward, certainly at GDS, you know, we've had clients that have been using open banking data now for many years. So certainly, I've been seeing a lot of adoptions there. Out of curiosity, did you build your own integration into the banking system? Or are you working with any of the aggregators?

Misha Esipov  31:02

We work with many of the leading aggregators. Our view is there are some great products out there that can provide that kind of highly reliable, base level connectivity. We think there's also a lot of a lot of value and being able to be compatible with multiple bank aggregators, which is what we've built. So, we work with many of the leading bank aggregators, and then everything that happens from there is all standardized. So, we classify the data the same way, through us through our engine, we build models and analytics and scores, build compliance and adverse action codes and all the buzzwords required to be able to use this kind of information in real time.

Rich Alterman  31:39

So, the Nova score cash flow. Is that aligned with a FICO advantage type scenario as well, and is it predicting the likelihood of default in the next 90 days?

Misha Esipov  31:49

Exactly. Yeah. So, we've spent a lot of time with one of, if not the best nationally representative sample of bank data, credit bureau data, to develop our scores and our athletics.

Rich Alterman  32:02

So, I know on top of that you then also have your income verification. Is that relying solely on banking data or are you also integrating with some of the some of the permissioned, uh, income and employment verification services like, for example, Argyle, yeah.

Misha Esipov  32:15

So, we work with multiple types of data sources, and maybe just to take one step back before we step forward. If you look at the income verification space, there's, you know, one gorilla in the room, who's been around for a few decades. That's the work number. You know, we're partnered with Equifax around the world. So, you know, I only wish the best for Equifax, but the reality is that that product line has limited coverage, right? Like, the big challenge for them is that they've only have coverage in the you know, I've heard different quotes from partners out there, but call it 30 to 42%, right? And that means that for 60 to 70% of your applicants, most lenders, go back to some manual process where you got to, like, upload some document, and it's a painful, not instantaneous, process. And so what we what we did is we created a product that has far greater coverage, north of north of 95% coverage of the US, adult population, using a intelligently designed workflow that combines bank transaction data, payroll data, different documentary types of being able to read pay stubs and bank statements and intelligently pull all of that together to create a best in class solution. So that product line has been one of our fastest growing product lines the last few years, doing millions of verifications now, and you know, we got connectivity into over 10,000 financial institutions, and it's one that, you know, we're super excited about.

Rich Alterman  33:42

So, you mentioned that you know in the US you are classified as a CRA I mean, you're fcr compliant, and also that I know you take on the responsibility because of that for dispute handling. I like to understand how you manage disputes related to credit bureaus outside the US and do any of them have any similar platform to what we have here in the US with e-oscar.

Misha Esipov  34:02

So, we do step into what it means to be a bureau in the markets that we operate in. We've built out and scaled, you know, consumer operations teams to help field the disputes that do occasionally come through. You know, the policies and procedures of those teams have been reviewed and audited by many, most of the big Bureau, all of the big bureaus by, you know, all, not all, many of the biggest banks in the world. And so, we've, we've really built this from scratch, in in house, using our own, you know, our own systems to ensure that we can meet the requirements of every market in which we operate.

Rich Alterman  34:39

Do you have staff outside the US, handling both sales, consumer dispute type processes. Or are you all here in the US?

Misha Esipov  34:48

Our head count is predominantly in the US. We have some components of our team in the UK, in Canada and a few other markets.

Rich Alterman  34:55

So, we've done GDS, we've had several podcasts that have touched on the use of. Alternative data. We've talked about open banking data, we've talked about non-prime credit data, rental data, etc., etc. I know you guys did a survey or contracted for a survey back in both 2022 and 2024 entitled the state of alternative data and lending survey report. Can you take a few minutes to share maybe some of the highlights and report and any interesting year-over-year trends that you found particularly worthy of discussion.

Misha Esipov  35:25

I think the biggest overall theme is that consensus among credit risk officers has shifted from one of skepticism to one of belief when it comes to alternative data, the importance of using alternative data to drive responsible growth. The term alternative data means a lot of different things to a lot of different people. I don't really like that term because I would argue many of these data sources, like bank transaction data and cash flow data or our global bureau data, which you could call alternative data, are equally, if not more, reliable than the traditional, traditional bureaus. And so, I don't love the term. I would rather just call it, you know, credit data, but it's what the industry is, is, is used to, and that consensus view has shifted in the last, you know, two to four to four, two to four years. And if you spoke with a panel of credit risk officers two years ago, and you asked them, you know, what are you working on? They would have all told you the same thing, recession proofing, recession proofing, recession proofing, recession proofing. And fortunately, you know, the recession has not come. And I don't know if it's early enough, if we're ready enough to say we're in the clear. We had our soft landing. I'm not going to speculate on the macro, but the sentiment has certainly changed from recession proofing to one of, okay, how do we start to open the box and use new data sources, new credit data sources, to do so responsibly, and so that, I think that's the overall theme. And maybe one more thought on that is, with 1033 open banking has arrived, and every risk officer and every bank is asking themselves the question, how am I preparing for open banking transformation? Right? What are the Strategic Initiatives I'm doing across the customer lifecycle, to use this kind of debt data, to cross sell, to pre-qualify, to better underwrite, to verify customers, more seamlessly, to do a better job down the customer lifecycle, with early delinquency monitoring and collections. There are so many applications for this kind of information, and if you're a bank executive or a risk leader who's not adopting and preparing to this major shift in the data environment, then you're not keeping up with the demands of what it means to be in that role.

Rich Alterman  37:53

So, with that, we'll let you put on a consulting advisory hat for a second, and you know, if you were talking to lenders that have never used cash flow underwriting. What are some of the best practices for them to move forward, to implement, of course, becoming a client of yours?

Misha Esipov  38:09

Well, I think your options are to try to figure it out in house, which will take a lot of capital, a lot of team, a lot of risk, a lot of time, and we can break down the puzzle pieces around how you integrate the technology, how you build a performance data set, how you train your attributes, how you build your scores, how you implement it, how you back test it. There are so many different components. And, you know, it's kind of, it's almost comical. The number of banks I spoke to two, three years ago who are like, you know what? We're going to try to figure this out on our own. And then, you know, check back in two, three years later, two years later, and say, how’s it going? Oh, we haven't launched it yet. Oh, what happened? And, you know, there's some narrative around, oh, our priorities changed, or this person left, like it's a really hard problem to crack on your own. And so, I think the number one best practice, or piece of advice I can offer, is to bring in an expert. Bring in someone who has successfully deployed cash flow underwriting the use of bank data at scale with other major financial institutions, and your path to value capture will be much faster, and your level of resource investment required will be much lower. And there are ways of deploying this kind of stuff with no code implementations that require zero technology investment, something you can now stand up in under a few weeks. And the market receptivity to doing this is only accelerating, and maybe I'll offer one more thought on this, that most credit risk teams really struggle with, which is kind of a philosophical point, but most teams allow perfection to be the enemy of progress. They're looking for that perfect model using bank data, and they're waiting for that perfect model with the perfect back testing before they deploy. And that pursuit of perfection comes at the expense. Process of making an incremental step and starting to learn and test and move a lot faster. And so, where we guide our partners is to start with something simple, and don’t over complicate the problem set. Don't get stuck in analysis paralysis and just get started. And once you get started, you're going to very quickly find ways to continue to improve. And you know, we often serve as a steppingstone to give teams the comfort for how to get started. And then we have a whole data science consulting arm that helps kind of SWAT team collaborate with teams to help them iteratively, iteratively improve.

Rich Alterman  40:33

Well, thanks for sharing that, and our listeners will take you up on that. I know on your website; you guys have a consumer section. You have a marketplace now that promotes different types of lending products. How would a consumer let, let's say that someone moved into this country and went to apply for a loan that doesn't use you all. How might that consumer come across you and get educated to say, hey, you guys need to be pulling my credit file from, you know, my prior company, country, and this company, Nova, can help you do that.

Misha Esipov  41:03

Yeah, it's funny this, this is one of these growth levers we've thought a lot about, but we haven't actually used all that much. And unfortunately, you know, the experience of an individual consumer is rare to shift the prioritization of, you know, a behemoth like a bank. And so, you know, we don't really leverage the consumer all that much to, you know, make a lot of noise to the bank and say, you should be using over credit. You should be using over credit. Maybe that's a fault on us for not figuring out how to do that more, more rigorously and methodically. But we primarily reach out. I mean, it's pretty out. You go into a new market, you it's very clear from the onset, with half an hour of desktop homework, like who the major lenders are, for whom you can create value, and we just reach out to those directly. We also get a lot of inbound from, you know, many of the regional banks here. And so would encourage listeners just reach out. You know, my email reached out to me on LinkedIn. You know, there's a lot to learn. Maybe you can buy some advertising space right outside of all the customs departments of the airports we have explored that.

Rich Alterman  42:08

Keeping an eye on the clock. Here we talked about the Nova credit platform, and that's a recent announcement that you've made. But are you willing to give us any quick insights into some of the things that you have on your product roadmap for the rest of 2024 and maybe into 2025.

Misha Esipov  42:25

Honestly, it's like, it's due less right now. There's, there's so much opportunity. And I think that stems initially from, like, don't try to recreate and launch a new, exciting product. It's really about going deeper into the three product lines we have, cash Atlas, cash flow underwriting, income navigator, income verification and credit passport, across border, data product all three of those sit on the platform. All three of those are available through, you know, through a single integration that we can configure. And so, it's, it's, it's all about getting deeper, Better, Faster, Stronger, cheaper, at doing all of those, those things. That's really where we're pointing at, you know, the product engineering, data science, design teams, and then on the go to market side, you know, we continue to focus on the US, you know, working with a lot of the largest banks, the non-bank lenders, and then we're going deeper into Canada, the UK and a few other markets.

Rich Alterman  43:19

And I'd add working with companies like GDS to do the integration into Nova and use that for part of the overall decision that our clients are looking to make. This is Rich Alterman, and we've been syncing up with Misha Esipov, CEO and co-founder of Nova credit, which helps lenders improve access to credit for immigrants and other thin no credit populations through its credit passport, cash Atlas and income navigator offerings. Thank you, Misha, for joining me today and providing the background and Nova credit and outlining its various offerings. I want to congratulate you, Nicky, and the entire team at NOVA credits, for all the success you have achieved to date. And I look forward to continuing to track your progress. We hope you've all enjoyed the podcast. Please stay connected with GDS Link and the lending link to listen to future podcasts and catch up on the ones you've missed. If you're interested in securing a copy of Nova’s the state of alternative lending in 2024 survey report, you will find a link included with this podcast, where you can secure it at nova's website, www.novacredit.com, I want to thank you all, and that's a wrap. Thanks for listening. If you've enjoyed today's episode, please be sure to subscribe on Apple, Spotify, Google or wherever you listen to your podcasts, and be sure to leave us a review. Follow us on LinkedIn and connect with us on Twitter at GDS link that's at GDS Link, have a question for the show, or have a specific topic you want us to cover, hit the link in the description to drop us a note. Thank you for lending us part of your day. Make it a great one. You.