The Power of Technology in Financial Inclusion with Dan Quan from NevCaut Ventures

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 Altman, and today we're diving into a variety of topics with Dan Quan, co founder and general partner at Nevcaut Ventures, including his experiences working at the CFPB the investment landscape of his new company, what industry trends he's expecting for 2023 and so much more. But first, head over to GDS Link's LinkedIn and Twitter pages at GDS Link and hit those like and follow buttons. Be sure to subscribe to The Lending Link on Apple podcast, Spotify or wherever you prefer to listen to your podcast. As I shared I'm being joined today with Dan Quan, the co founder and general partner at Nevcaut Ventures which launched in May 2021 and invests in early stage fintechs. Dan is also a Senior Advisor for Mackenzie's banking practice since 2018, and an adjunct scholar since 2019 at the Cato Institute's Center for Monetary and Financial Alternatives. Dan holds an MA in public administration from Harvard's Kennedy School of Government and an MBA from Drexel University's Bennett Lebow College of Business. Dan also sits on several advisory boards including pay active. Alright, now let's get synced with GDS Link. Afternoon, Dan, and welcome. Thank you for having me. Rich. One. Thank you for joining the Lending Link today. I'm really excited to have you with us. Where are you joining us from today? I'm actually in Jacksonville, Florida. No hurricane. Everything is very peaceful here. Before we jump into the business side of things, I always like to get started with a little personal opportunity to learn more about our guests. You shared with me that you were born in China, and you moved here in your 20s, can you share any specific feelings you had when you first arrived in the US?

 

Dan Quan  02:07

What do call FOB right? Fresh off the board a boat. And even though I did study and learn English, we're, I don't know 10 Some years in China and still speaking the language as a second language when you constantly had to do the translation in your head before you open your mouth. That was a challenge and a while English is still quote unquote, my second language it's not my mother tongue. But I think over the years, you the translation process became not noticeable anymore. And someone actually told me that that when you speak English in your dream that means you have you have already, you have already been you know, sort of mastered the language already. But I did a few times. A couple years after I arrived in this country. I in my dreams, I will speak English. So I guess I already arrived. At that point.

 

Rich Alterman  02:57

You also share with me that you enjoyed traveling. If you could only go back to one place that you've been to before. Where would that be and why?

 

Dan Quan  03:04

Bhutan definitely Bhutan if anyone for anyone who has never been to Bhutan or don't even know where the country is. It's a tiny, tiny, landlocked landlocked country between China, Tibet and India and Nepal, I think. Yeah, I think the bordering Nepal a little bit. Anyway, it's quite expensive to actually be in the country, because they actually has a bit of a minimal spending for foreigners, because they won't actually keep the country pristine. But they're very friendly people very friendly, you know, government there, but beautiful scenery, places really beautiful, very, very peaceful, tranquil.

 

Rich Alterman  03:37

I'll add that to our bucket list. My wife and I just got back from Greece in Turkey recently. We had a great time there. Well, thanks for sharing that. I always think it's good to see the human side of my guest. But let's get down to business. Now. Clearly, you have a very diverse background, having worked both in the private sector, as well as the public sector. Today, I'd like to start off discussing some of your work at the CFPB. I see from your LinkedIn profile that before you joined the CFPB, you were a research associate at the Harvard School of Business, can you share the type of research you did, and whether this work was a catalyst for wanting to take a role at the CFPB.

 

Dan Quan  04:12

So I was a student research associate at Harvard Business School and it was working for a professor, his name is Peter Tufano. At that time, he was a senior senior associate dean at HBS. And he was actually about to leave and became the Dean SIE business school at Oxford. So that was his last year at HBS when I worked for him. And I was in my mind, you know, my math is pretty good. Not not top notch, but pretty good. So maybe teaching economics is something that's been sort of always appealing to me. So that's how I became his assistant and helping him with the research. So now the interesting thing is, in those days, when you talk with when you think about finance at elite schools at HBS it's all about the investment banking You know, hedge fund PVC. Nobody really nobody thought about Main Street customer banking, like credit cards, debit cards, loans, mortgages. But Peter was the first one that actually introduced a consumer finance course to business school, not just in sort of top ranking schools, but business school period. And I didn't know much about customer finance, even though I did have a credit card, credit cards, but just one credit card account, a checking and savings accounts. But he really is sort of taught me about these things, which are, frankly, quite foreign to me, when you actually dug deeper. So he wanted, he asked me, Do you want do you like teaching? And I said, No, not really do like doing research. I said, well, not really. They said, Well, why are you wasting our time and money to make your PhD candidate. And I was like, most PhD students end up not end up end up in Wall Street or elsewhere, not in academia,  at least on the application, they were saying they wanted to be professors. Right. So essentially, I said, a lot. I'm being penalized for being honest with you, you know, how about this little agency, new agency called Consumer Financial Protection Bureau, and he was actually helping them on some of the efforts as they were starting up, and go check them out. If you're interested, you know, I'm happy to make a connection for you. So that's how I actually moved from Boston to DC. Now, thinking about the work that I later did at the Bureau, actually, for the majority, majority of my time I did in the Bureau, which is about innovation in 2010 or 2011 he and a bunch of other professors  wrote a letter to then directory that that was Warren not Senator, actually strongly urging her not to just simply focusing on enforcement tools and supervision tools, to sort of, you know, get rid of bad actors. They encourage her to really think about innovation, which is something that policymakers and regulators, at least at that time, nobody was even thinking about that there's a softer approach, right? So the idea is, enforcement supervision are very effective, but blunt tools to get rid of bad actors. But at the end of the day, financial regulation basically only serves as the minimum threshold that everyone has to has to abide by, right. So it's the minimum standard that you have to comply with. But how do you encourage firms to go beyond that? And you can, you can actually kill or ban all the bad actors. But the end of the day, consumers still need a good financial product to, to use. So they buy. So they strongly encourage her to really think about ideas like innovation. And I shouldn't say that letter was the catalyst for Project capitalist. But that definitely, served that you know, I think it was one of the reasons. And Peter later on, after I took the job, actually, I he was already over the pounding at Oxford. I connect, I reconnected with him. And he said, Well, I should take credit for the job you're holding today.

 

Rich Alterman  08:00

Yeah, so that was around 2012, when the CFPB announced Project Catalyst. Yeah. And I think you kind of talked about the mission, it was around innovation. Any other tenants that were the key objectives for Project Catalyst. I know one of the big things for the CFPB is all about financial inclusion. So was that one of the key tenants as well, that you could talk to

 

Dan Quan  08:22

Somebody at one of the largest financial firms actually told me this was when I was CFPD. He said, Well, you guys are taking a very sort of, for lack of better word casual approach when it comes to interacting with with us casually, not not in the sense that you're being on no serious casual means you're being approachable, will be approachable is a better word. So he gave me example where how they engage with another agency, whose name I shall not mention. He said, they have to go through first first step has go through their examiner, the examiner would relay the request to the field manager, field Manager will request regional director, then Regional Director will contact the senior staffer in DC in the headquarters to help set up the meeting. So from the time they want to have a meeting with a senior staffer in DC, till the meeting happens, typically two to three months. Whereas the CFPB with us was was much, much faster. And we realized this is something we should issue. We should be doing more as an agency because, you know, everybody lives in their own bubble, especially in Washington, DC, you don't know what's going on outside the beltway. And when we started seeing innovation popping up everywhere after the financial crisis, when the incumbents basically retreated right, so all of a sudden, this new thing called fintechs came up. Right? Remember in the days Lending Club was was Lending Club and prosper. They were the first innovative companies that really even the incumbents launch when it comes to lending personal loans.

 

Rich Alterman  09:55

I recall that prosper rolled out first right and really had some challenges in th regulators to understand who and what they were.

 

Dan Quan  10:03

Yeah, they were they were shut down by the SEC and right Lending Club, a volunteer and they cease their, their their business for a year. So all these earlier pioneers had challenges in all sorts of challenges with regulations. And I think it's good thing that the Bureau's leadership back then, you know, Director Cordray, he realized this is something we need to fix. So how do we do that? Right? So the first thing is really about information gathering. There's a huge information gap, the startups or the, you know, the guys were just who wear jeans, they have no idea what kind of regulatory expectations they should meet those who are like, you know, the CFPB, and other agencies who are writing the rules, were enforcing the rules also do not understand how these rules are affecting the sort of innovations, are they helping them? Are they are they are they hurting them. So I think that was one of the reasons project calendars or Office of Innovation, they know it was called, was created just to gather information, just be approachable, really, back in a day, if we actually had this sort of informal dress code, when you meet with these guys, especially when you, you know, go to San Francisco or other cities, New York, you have to wear jeans, don't wear a suit, don't wear tie, because you're going to scare people off. But of course, when the initiative was initially was first launched, the mission was to promote customer friendly innovation, right. But it's a very vague term. But in reality, when the first thing we did was just trying to get people to talk to you. Because people are afraid people are very, very afraid, especially as you know, in the early days of the CFPB, there was not the negative press coverage about the bureau, it was hard job just to to make sure people are willing to sign up and to meet with you and to later on divulge information that you otherwise will not be able to hear.

 

Rich Alterman  11:42

So undoubtedly a lot of our listeners today are familiar with the initial no action letter that was issued to Upstart. So in 2017, they were issued the first new action letter which was related to the use of alternative data. In making credit and pricing decisions, I can actually remember reading some of the papers on alternative data surveys that were done. And then a second letter in November 2020 was related to the use of AI and machine learning in model development. And then 2022 Upstart actually requested that the term the letter be terminated, when you look back and you share the positive that you feel came from these no action letters. And what were some of the lessons learned as you and your team evaluated the extension of other no action letters at the time.

 

Dan Quan  12:26

So if you go to an agency asking a question,most of the times, they actually will stay silent, they will not tell you what is legal or in compliance, they will just don't tell you anything. The reason being, they are afraid to tell you something that could be, you know, interpreted as something like a blessing or endorsement. And also, most of the times they just do not know the answer. And I think the notion that our tool was really initially designed just to try to really bypass a problem, right? So if you look at the policy, the policy basically doesn't say yes or no policy just says, again, very vaguely, the CFPB will not take adversary actions against you. But of course, the bureau will have the authority to you know, rescind the letter. So we saw the use of AI and machine learning, and the use of alternative data that can potentially expand access to credit. And the CFPB has done lots of research in that right that the credit invisible. The term was basically coined by the CFPB research group. But now, is there any regulation that specifically bans the use of AI and machine learning alternative data? The answer is no. Everybody is concerned about obviously, discrimination of disparate impact. But the regulation doesn't say you shall not use certain data, unless it's expressly prohibited by the law rights like race, age, gender, and other protected classes. So there's a lot of hesitations, I personally feel the letter has already served its purpose. But what I really want to see wanted to see actually, when I saw the second letter coming out, I should be able to, you know, want to save up to write something to issue something as broadly applicable to the entire industry, not just specifically to a company, right, like Upstart, I really hope that the letter is nothing but a tool. It's not the end game, right? The end game is how can you really learn from these experiments, these tests and figure a way to provide broader guidance to the industry so that everybody can benefit from it. But at least there was an experiment, there was some lot of empirical evidence that shows machine learning and the use of non traditional data, if properly supervised and managed, does have the ability to expand access to credit without triggering any kind of negative consequences. Not the vendors afraid of

 

Rich Alterman  14:50

Yeah, I mean, I know that you are you talked a lot about when you and I chatted before about open banking data, and certainly we've seen explosive growth right? In that use of data, and certainly, it's allowed for a lot more inclusion of consumers that otherwise might have been denied. Kevin moss and I talked a lot about that on the last podcast. But you mentioned, you mentioned Dan, disparate impact. And that's a topic that, you know, is often talked about, I still think there's confusion in the market, I've asked the last people in the world to say, you know, explain to me what disparate impact really means. And how do you detect it? So, you know, when we think about machine learning and AI, in particular, do you feel that the application of those tools is doing a good job to ensure that there isn't a disparate impact? And is it really something easy to determine?

 

Dan Quan  15:44

It's not easy to determine? Frankly, it's very, very difficult. And if you look at the sort of still permitting practice of how lenders do disparate impact testing, it's a very much a manual process, right? You hire lawyers, you hire those special specialty firms that have lots of expertise. And they have the columnist with PhD degrees, crunching numbers, developing models, into the swipe in, swipe out. And it's a very, very labor intensive exercise. And I don't think it can really go scale. And the lenders are scared of it. So if you look at the original intent, intent of equal credit, Opportunity Act, that UCLA or you Cola, there were actually two purposes. One was really tried to ban the discriminations. Things like women shouldn't get credit, right? Back in the days, that was the law. Now, it's like, oh, that's definitely illegal, right? Black people, people of color shouldn't get credit. That's definitely illegal. But back in the days, that was the law. So that was the first thing that the act was trying to fix. The second thing, which actually, over the years and decades, since the ICO was passed, nobody really paid attention to it, which is really, how can we really unlock the credit box, expand the credit box so that more people can benefit, get access? You know, that's a really important factor for people to move up the social ladder. So as a result, I think lenders become extremely conservative, you know, they stick with the playbook that they're they're used to right, and they're afraid of making any changes, and the result is still one of the wealthiest country in the world, we still have over 40 million Americans who are credit, credit invisible, that's a shame, really ashamed. And the machine learning obviously, can help solve that problem. Does it solve all the problem? I don't think so. But actually, that has the potential to really open up the credit box. But it's not a panacea, it doesn't cure all the problems, for sure. But machine learning definitely can really help solve some of the problem. The positive side is that regulators are aware of what's happening. And there are lots of groups that are trying to do research to get a better understanding of how AI ML can be helpful. And you saw a couple of weeks ago, the White House published the Bill of Rights for AI, which I think is all positive, right and nothing, nothing earth shattering from that from the document. But actually, that's that, that lays out some very good principles, how, you know, not just financial services, but generally, companies should private sector companies should, you know, should pay attention to when they adopt AI and ML. But I think at the end of the day, everybody's concerned about discrimination. Nobody wants to discriminate, right. So I think regulators need to really provide a better guidance or roadmap for compliance. And I'm not really banking on any agency in the near future to issue such guidance. I know the agency has tried in the past, and they really tried to collaborate with each other. But I think at the end of the day, they're doing what I call a job that's like Mission Impossible. The reason I'm saying that is, unlike most of the regulations in the United States, when it comes to federal lending, disparate impact, it's very much principle based. So the law, the rule, that is say, here's a red line to cross it. Right? There's no guideline. So you don't know. You don't know until you get a CID or you get the investigation. That will be too late.

 

Rich Alterman  19:07

There's always that level of uncertainty on how far you're straying? Yeah, interesting. Exactly. Yeah. So kind of wrapping up on the CFPB. There's been a lot of news that the CFPB over the last couple of weeks. And, in fact, this week, they announced some rules that they're looking at related to 1033 and the personal financial data rights. What are your thoughts on that? Is that something that we'll see come about and understand that really about giving consumers a lot more control over their data, creating a lot more competition? I read an analogy that talked about the portability of phone numbers, and how that law allowed people to easily switch from Verizon to T Mobile, and that the goal here is really to allow consumers to more easily hop around if they're not happy with the service or getting from a particular financial institution, you know, your opinion on, you know, when when do you think we'll really see a reality of that happening with the rules?

 

Dan Quan  20:10

Well, I'm not sure if the rule is ultimately going to be able to achieve that, I think, you know, switching from number switching waters provider, while keeping up the number is much easier task than switching your depository institution while keeping a direct deposit and payroll and all the other billpay information intact. I think these are two different things, very different similar things theory. But the latter is much, much more complicated. And I'm not sure that rule will actually achieve that. But we will definitely well set up a regulatory framework such that when consumer permission, third party to access their data on their behalf, as if they were the one that you know, access their information and using their mobile app or the online banking portal. I think that's really the first step back in 2016 13, when we saw open banking, PSD to open banking in the UAE, in the UK, and that's PSD to yio. We realized that, you know, in the United States, we don't have any of these rules or regulations or sort of, you know, mandates, but we have this thing called tattly. Three, which is something that no most people didn't even pay attention to. But on the other hand, I think United States has always been at the cutting edge when it comes to data sharing. I recalled six years ago, around this time Director Cordray went on Monday 2020 and deliver a speech. And toward the end of the speech, he basically said that data belongs to consumers, and that they have the right to share with third parties. So so that was the first shot, he fired. Roosevelt across the board. Exactly. And six years later, we finally the agency is moving on to a official Google Making a well I'm very, very happy, even though it's you know, I wish this could go faster.

 

Rich Alterman  21:53

Well, we're going to take a moment to virtually take off your public sector hat and put on your private sector hat and talk about your new business. Nevcaut that you launched in May 2021. Interesting name, why don't you share a little bit? What is Nevcauat mean?

 

Dan Quan  22:10

Well, obviously, you know, as you mentioned earlier, at the beginning of the show, this venture fund really focuses on early stage FinTech InsurTech. Startups. So for anyone to invest in that stage, you got to be bold, you got to be willing to take risk, not just startup founders, but also investors. And we, we haven't to be in a camp. And we would love to roll up our sleeves and fight in the same trench with the founders that we support. And we want to be bold. So we want to be cautious, of course, but we do want to be too cautious. So Nevcaut is kind of never cautious. But we're still very prudent with our LPs money, that's for sure. But we have done some very, very good deals, and we're happy with the portfolio we're building so far.

 

Rich Alterman  22:56

You know, as you evaluate companies, you list out the different firms you're involved with on your on your website, how do you feel that your experience at the CFPB is affecting or impacting what companies you decide to invest in? One of the companies you've invested in is Fairplay, which is about fairness as a service. So you know, maybe kind of talking about what's that influence that the CFPB days for you have had, when you're looking at firms that you might invest in?

 

Dan Quan  23:24

I think at the high level, you know, I think a VC business is more or less a insider business, right? So you know, the network, you know where to find the deals, you build your network, you build your name, to build your brand, so that founders want to work with you, what they seek from you is not just a cheque, they actually want advice. So I think a lot of the work that I've done at the CFPB some of the pioneering work in in the use of data, you know, machine learning and AI, as well as open banking, that really has translated into very valuable advice to founders that we're investing in the founders that we work with. Glad you mentioned fairplay. So, you know, this is really sort of a continuation of my previous work at Bureau, AI machine learning. And I'll just repeat which we just talked about. And I think fairplay really their solution is really is revolutionary in the sense that a lender can really do disparate impact testing on demand. It no longer need to hire expensive lawyers and consultants to help you. And it will take them three to six months. This one if you use their software you can do with it within, you know, a couple of hours. You can do it constantly. And this is something I actually when we when we first look with upstart we were wishing that there was some kind of solution like this, because you think about it. The lender doesn't know. He is, you know, violating ECOA until they until after the fact right because for the longest issue, we have no idea whether you're in compliance or not. Even if today or after you look back for six months, you are in compliance, that doesn't guarantee you'll In other six months, you are still in compliance. So ideally, regulators should require vendors to do constantly testing of their disparate impact compliance. But no lenders does that, because it's very, very expensive. And I think fairplay can really do that. And I think just beyond also beyond just lending, furnishing, doing business is about marketing, it's about insurance as well. So the app and the application of their of their software, it really goes beyond that. Purely disparate impact testing, which is always very, very, you know, technical and hard for people to understand even for, for equity investors. The third thing I think, about fair, fair play that sort of got us excited, excited, is really, and we talked about this rich, earlier in the show. So folks like you and I, whether you use fancy machine learning tools, or alternative data, the result from vendors perspective will be the same, we probably get the best interest rates, the largest line, we can see. Right, but for the people who are poor, actually on the edge, the results will be very different. And the you don't know whether a 600 FICO is necessarily better than 580 FICO, right? But if you surely look at, you know, traditional using traditional regression model, and, you know, traditional data sources, sixth one, there probably is a better risk than 580. But I think, once you apply machine learning, you may see different results. And I think that's their second look product is going to be if lenders are, if they can prove, you know, their their their accuracy, I think lenders will find it very, very useful for them to really, again, more precisely manage the portfolio risk, and all at the same time, without increasing the default risk and opened up the credit box to allow more people to get credit.

 

Rich Alterman  26:43

Interesting. Yeah, so I kind of think about a guy and theory him right that our second look lenders, but this would be an opportunity for the first look lender to go deeper by looking at these type of opportunities. I'm sure you're familiar with Nova credit, right? I mean, there's no credit to Nova credit at for our audience, they've built a platform that helps people immigrating, or immigrants in the US get access to their traditional credit file somewhere else in the world. And they formed the alliances with several companies, they're doing a really great job. So this might be a little bit of a personal question, but I think about your viable project catalyst, your role as an adjunct professor with the Center for monetary and financial alternatives, fair play, I get the feeling that you're kind of on a mission related to financial inclusion and fairness in lending? Would you agree with me? And can you share why you're so passionate about the subject?

 

Dan Quan  27:35

And the answer is, yes, it is. When we raised our phone, you know, 1818 months ago, financial inclusion is one of our core thesis for the fund. And obviously, as an investor, we ultimately want to return the capital to the LPs with, with multiples on it, right, hopefully, but we do really believe that was the power of technology, financial innovation, I think financial services can be more fair and more inclusive. And at the end of the day, at the end of the day, you know, as investors, we can make a lot of money by doing good things. So probably just, you know, as a, as a new immigrant to this country, myself, right, I lived through poverty myself to you know, at a time when I had to borrow a lot of money just to, to maintain my lifestyle, because, you know, lost my job couldn't, you know, without low, I wouldn't be able to survive another another Another week, another month. So I was keenly aware of how important the access to credit is just a short as through personal experience. And also, I can still remember the first time I got a credit card, you know, I've no idea what credit card was, when I first moved to this country. I kind of had some idea of a debit card, but never use debit card in my life. Before that. When I was in China, some credit card was like, wow, I can borrow money on this piece of plastic. It's amazing. If I cannot describe to you how how much joy I I had when I open the envelope, and some kind of institution I think was MBNA, which doesn't exist anymore. Give me a car and leave the inmy that you know, you can because spend the money responsibly and pay me back right because I was a thin file no file at that time. I can tell you another story where we we did a deal. Investing company got funded, right. So Steph, Steph sample this is the Founder CEO. The mission of the company is just trying to provide the credit to women owned small businesses, right, which is hugely neglected. And when she sort of described to me when she had a pitch to me, and I just that sort of what she described to me as her she herself was a has been a small business owner for her life. My experience personal experience, its consumer, sort of, you know, fresh off the boat and on good credit that I can very much resonates. And I really believe that credit can be more fair and the credit can be more open and more people can benefit more business. Small Businesses can benefit from it. And what we need is really right investments. Why founders? A why regulations?

 

Rich Alterman  30:07

Well, it's interesting maybe if more people saw opening that credit card as a privilege and not as a right, might be a better one on how they make those payments. So kind of wrapping up on the business side, as you think about firms that you might be investing in companies that are out there looking for capital, obviously, we're in a lot different market today than we were six months ago, 12 months ago. Any advice that if you know, if you are about to interview, a startup, what is some advice that you might give them when they're about to come on the Nevcat Shark Tank?

 

Dan Quan  30:41

Well, I think the first thing is lower expectation. Lower expectation, and don't be don't feel offended when the VC pushes back on the valuation. And I think we we got a lot of pushback, you know, a few months ago, but I think now a lot of founders sort of the kind of syncing with the reality it is a different environment. And, and you really be prudent with with the money that you're you want to seek, you know, from from the investors. And yeah, I think the winter is Winter is here, and the winter is here to stay, it's not going to be a I'm not talking about the recession, pending the company, 10 recession or anything, it's really bad, just the the winter in the funding market, probably the market is not going to recover anytime soon, you know, we'll continue to see low multiples, depressed valuations, and unfortunately, good ideas not getting funded. And they just go belly up. And that's very unfortunate. I think, as you know, there's as well, a lot of VCs are really holding cash, and they're sitting on the sidelines. And I think, hopefully, six to eight months, we'll see some kind of loosening there. And you know, VCs are more willing to deploy capital, because at the end of the day, right, LPs give you money not to sit there idle and collect management fees, they want you to invest. Right, I think that's going to change, but I'm not sure how quickly the change will come.

 

Rich Alterman  32:05

Well, I guess if you could get that capital today, you're gonna have to have, as you say, are stronger selling position.

 

Dan Quan  32:12

I'm glad you mentioned that. So now the another advice I always give to startups that we work with is, which is if, if someone's willing to give you money, write your check. Take the money now. Don't worry about dilution, unless it's ridiculous terms. Right. But right, most VCs are being reasonable. They're not. They may be aggressive. You'd rather be you know, you're the rather the owner of 1%, owner of a billion dollar company, then 100%. But you know, I'll feel the business. Right, right. Exactly.

 

Rich Alterman  32:45

Good. Good. Great. Well, this is a Rich Alterman, your host of the lending link and talking to Dan Quan of Nevcaut Ventures and prior member of the CFPB. Dan, thanks for joining us today. Hope you've enjoyed this as much as I have. And maybe we'll have you back sometime in the future and good luck with your new company.

 

Dan Quan  33:03

Thank you for having me Rich