Anyone who has applied for a home mortgage (unless it is from one of the new fintech lenders) knows how painful the process still is today. It is somewhat crazy in our instant, on demand world that it can take 60 days to close on a mortgage today.
Our latest guest on the Lend Academy Podcast also thought it was crazy and decided to actually do something about it. Vishal Garg is the CEO and Founder of Better Mortgage and a few years back he missed out on buying his dream home because of the clunky and slow mortgage process. So, he started a company to completely turn this process on its head.
In this podcast you will learn:
- How the experience of losing out on a house to an all cash buyer led to Better Mortgage.
- Why one of Vishal’s first moves in setting up his company was to buy a bank.
- The major problems with the mortgage application process today.
- The typical cost of a mortgage at a major bank.
- How Better has transformed the mortgage application process to make it better.
- How they work with the largest lenders in the country.
- The scale they are at today.
- Who the typical customer is that comes to Better Mortgage today.
- How they can underwrite a loan in just one day in six markets right now.
- How they can provide a loan from Citi, for example, for a lower price than going to Citi directly.
- The level of automation they have in the underwriting process.
- What Vishal means when he says they are building the “Amazon of Credit”.
- How Better makes money.
- How they are capturing data to add rich context for every borrower.
- What Vishal is working on that makes him most excited.
This episode of the Lend Academy Podcast is sponsored by Wunder Capital: where impact investing meets capitalism.
Download a PDF of the transcription of Podcast 138 – Vishal Garg of Better Mortgage.
[expand title=”Click to Read Podcast Transcription (Full Text Version) Below”]
PODCAST TRANSCRIPTION SESSION NO. 138-VISHAL GARG
Welcome to the Lend Academy Podcast, Episode No. 138. This is your host, Peter Renton, Founder of Lend Academy and Co-Founder of LendIt,
Support for the Lend Academy podcast and the following message comes from Wunder Capital, the easiest way to invest in large scale solar energy projects across the US. With Wunder, you can help finance renewable energy projects while earning up to 7.5% annually. To get started, visit wundercapital.com/lendacademy. Wunder Capital, where impact investing meets capitalism.
Peter Renton: Today on the show, we are talking mortgages and in particular talking about revolutionizing the mortgage application process. So I’m delighted to welcome, Vishal Garg, he is the Founder and CEO of Better Mortgage. Now as I just previewed, Better is really doing something that many would have considered impossible just a few short years ago. They’re basically taking the mortgage application process which has been a painful and arduous experience.
I’ve been through it several times and every time it has been painful and arduous. They’re making it into a quick and simple and even somewhat enjoyable process and how they’re able to do that is really the subject of this podcast; it’s a fascinating story. We talk about technology, we talk about data, we talk about underwriting and we talk about the consumer, what they want and how Better is able to deliver what they want. It really was a fascinating episode, I hope you enjoy the show!
Welcome to the podcast, Vishal.
Vishal Garg: Thank you so much Peter for having me, really excited to be here.
Peter: Okay, so let’s get started by giving the listeners a little bit of background about yourself and what you’ve done in your career to this point.
Vishal: Thanks, just a little bit of a background, I started my career in fintech almost 20 years ago, I think before sort of even fintech was a word. I was an Analyst in the mergers & acquisitions department at Morgan Stanley, I dropped out of the analysts program after a year to start a company called MyRichUncle.com which was the first online student lender. The original product was we would give kids money for college in exchange for a percentage of their income. Then over time we built a dataset of outcomes post graduation which we helped to basically create the first direct to consumer online student loan company, eventually took that public in the mid 2000’s, sold a chunk of it to Merrill Lynch in 2007 and they became the majority investor in the company and then in 2009, they shut the company down.
I spent 2009 to 2013 building up an asset management business, got to about $6.5 billion in asset management mostly taking social media data and applying it to mortgage-backed securities and student loan securities, asset-back securities and effectively using that to better underwrite and trade the securities.
Then I went to go get a mortgage when my wife and I were pregnant, my wife was pregnant with our second child, and we were looking to buy a home and I found that process so frustrating and basically used the experience I had in both the finance side as well as creating consumer internet companies in financial services to launch Better.com.
Peter: Okay, you got the idea for your company and then from what I understand, you go ahead and buy a bank in 2015 which I thought was a curious move. Tell us a little bit about that time period and why you decided to go buy a bank.
Vishal: What ended up happening was I started researching the mortgage business. I got curious when basically we lost our house that we were going to buy to basically a broken mortgage process, to an all cash buyer and I was both frustrated, but also so intrigued, I was like how is it that mortgage is so bad, why are they not better. There are all of these companies revolutionizing the delivery to consumers of credit across a variety of asset classes, but it seemed like mortgage was totally untouched.
So I had researched about 20 different mortgage banks and started diving in a little bit and realized that fundamentally creating something from scratch was going to be a really, really tall order because of the regulatory requirements which are on a state by state basis; there’s effectively no federal preemption and then on top of that, the localized nature of the market. So I thought what would actually be best is to takeover an existing mortgage company, one where all of the pieces were connected from consumer to end liquidity provider, and then take that and effectively fully digitize it and then over a period of time, automate it.
So that’s what we decided to do is actually take over an existing mortgage bank that had been in operation for about ten years where the principals knew that the world was about to change, but weren’t able to really build the next version of it. That gave us a real head start in getting going.
Peter: Right, right, that makes sense. So then I just want to step back a little bit. I went through the mortgage process a while ago, it’s been a little while, but I’m curious, from your perspective, what are the major problems in the mortgage application process today?
Vishal: Yeah, so I would say that there’s two major problems, right. One is speed and certainty and the second is cost. So the first problem, speed and certainty, a mortgage company on average can’t tell you whether you’re going to get the mortgage or not for anywhere between 30 to 60 days so you’re shopping for a house that you don’t actually know whether you can actually buy the house. That’s because at most banks the process is totally disconnected so you have a loan officer who is usually a commissioned counterpart and they’re really like a salesman, they’re out there “hunting”, either by talking to realtors and trying to meet customers as they’re shopping, or by sitting in a call center and buying leads from companies like LendingTree and the like and, you know, calling customers all of the time.
That person is good at selling, they’re not really good at advising and they’re not really good at processing and underwriting. So what happens is they collect a few pieces of customer data and then hand it over to a processor. Then the processor compiles a bunch of documents and then hands it over to an underwriter and the underwriter hands it over to a funder who then hands it over to a closer and these groups at the banks number in the thousands. It’s basically mostly people taking a PDF from somebody else, adding a few pieces of data to it and then verifying it with a third party source and moving it down an assembly line, but none of them is talking to each other.
And none of them actually has the ability to do anything or change anything in the process so if there’s anything that goes wrong, you basically start from scratch all over again. That means you don’t know where you’re at in the process and you don’t actually have any certainty that it’s going to close or close on time. So it creates this huge stressful process that then gets to the second point of cost. At an average mortgage bank, it costs $8200 to make a mortgage.
Peter: That’s crazy.
Vishal: That’s crazy, right. So in what it costs like Hyundai to make a car and ship it across the ocean, a typical mortgage bank generates a PDF…
Vishal: …that you sign, at closing.
Vishal: And that’s mind boggling and it’s even worse, you know, at a big bank that number might be $15,000. So if you think about that, the average mortgage in America is $250,000 so $8,000 of manufacturing cost is literally three points.
Vishal: That means…and that translates into Americans basically paying 1% more per year simply because of the commissions and the costs than they should be. Can you imagine that, $15 trillion, the largest financial asset class in the world, right. 85% of consumer finance, literally is 1% or $150 billion a year more expensive for consumers than it should be because of the commissioned loan officer and the broken process.
Vishal: And so we thought that there’s this real capability to change all of that and give that savings back to the consumer and actually let people buy a better house.
Peter: Sure, so talk us through then how you are actually making the process better.
Vishal: Sure, so what we’ve done is effectively built a rules engine. So what we observed is in mortgage, unlike many of the other asset classes, most of the credit risk is absorbed by the GSEs, Fannie and Freddie, or the FHA or the VA or any of the other mortgage insurance companies. So fundamentally, it’s about surfacing consumer attributes, surfacing property attributes, verifying those and then matching them to the best end investors’ preferences and those preferences take place at an attribute level and at a price level and then building this three-way matching engine.
In fintech, others have built sort of originally, in their original incarnations like Prosper, Lending Club, Zopa built, you know, what P2P…basically was a single person to investor matching engine. A three-way matching engine because of the recursive nature of a three-way matching engine is a little more complicated, but that is effectively what we’ve built. And what that allows us to do is take the bulk of that cost out of the transaction, save the consumer time and actually provide certainty because we know that the match is perfect, whereas your typical mortgage broker is sort of just throwing spaghetti against the wall into the process and hoping that it sticks all the way through from loan start to loan closing.
Peter: So how do you know that the match is going to be perfect?
Vishal: We know that the match is perfect because the engine that we’ve built on a rules basis is effectively taking the data from the consumer or getting the data direct from the source and so we’ve built APIs into all of the different places where you’re going to need sourced data, whether it’s property data, title data, appraiser, valuation, paystubs, tax returns, all that. And so we know that we’re getting the data from the end source rather than from the consumer or having to ask the consumer for it and then what we’ve built on the backend is actually an investor rules engine so we built our own interest rate engine, pricing engine as they call it in mortgage technology, and we’ve built our own underwriting engine.
So effectively, what we do is we’re not like many fintechs at the backend who typically like create clusters. So, you know, let’s say a Lending Club or others might create a cluster and say this is Grade A, this is Grade B, Grade C, but you might remember and you’ve been doing this for a really long time as well being there right at the beginning. Originally at Prosper, you could actually just say…hey, I only want to lend money to people whose last names start with R (Peter laughs) and that have this attribute and this attribute and that attribute and that’s what we did.
We built that matching engine at the back-end so an investor…we basically take the investors and we have 21 major financial investors, we’re the only fintech that’s a direct Fannie seller/servicer so including, effectively, the biggest GSEs. So 70% of the mortgage market is on our platform so we have now $700 billion of capacity on our platform from the investor side and each of those investors, we take their 200 page PDF underwriting rules and we manifest them in our platform. And because the match is totally digital, it’s perfect all of the time.
Peter: Okay, I presume you’ve some of the bigger, the Citi’s and Chase’s of the world, obviously you can tell us, but…so you obtain the information from the mortgage applicant and you’ve got all the data that you need to pass to Citi or Chase or whoever and they can make an instant decision? Is that what you’re saying?
Vishal: No, it’s actually better than that. I don’t pass any of your data to Chase or Citi or Wells. I know they’ll finance us to make the mortgage to you and I can make that decision instantly and I know not only will like Chase, Citi or Wells finance you, but also PennyMac and Fannie Mae and a whole bunch of other people and by the way, we can then say…actually, PennyMac really wants to find loans for consumers with these attributes who are buying townhouses in this particular area and so we can pass on that savings directly to you.
Peter: Okay, so you’ve basically got agreements with all these organizations and they’ve basically given you the authorization to make these loans. Is that how it works?
Vishal: That’s correct, that’s correct.
Vishal: They’ve given us 100% certainty that they will finance us making these loans.
Peter: Right, right, okay.
Vishal: And then fundamentally, the best thing is we are direct Fannie seller/servicer so we have a direct, you know, one of the counterparts effectively providing us a guarantee of financing is Fannie Mae which is a government-sponsored enterprise.
Peter: Right, right. So you said you’ve got $700 billion of capacity now, I imagine you’re far less than that. So you’ve got all of these companies lined up. I mean, can you give us a sense of the scale that you’re at today?
Vishal: We’re on track to do a billion of loans this year.
Peter: Okay, okay, so you’ve still got some runway to go, but you’re certainly getting into some serious numbers there. Okay then who is the typical customer for you guys, I mean, who comes and applies for loans?
Vishal: Yeah, so we have the customers that discovered us and really whom we are amazing for is a first time home buyer or someone refinancing for the first time because when they’re going through the process they have such little knowledge about how bad mortgages are…
Vishal: And how bad the process is about to be. You know, fundamentally, a lot of them think or they talk to their parents or others and they hear bad stories or horror stories. Our engine is very powerful for them because most of these people have attributes and characteristics that are very different than the attributes and characteristics that their parents had and your traditional bank or mortgage company can’t even fund that or more importantly, your traditional mortgage bank or mortgage broker, the guy sitting in the branch at Citibank or Wells Fargo cannot even surface all the permutations and combinations of product types that are actually available so they have a different expectation.
The consumer is not….while they want support and they want help, the banking system is basically unable to kind of service them so we are really great for people whose balance sheets look very different right, the traditional mortgage process is built for a 20% down payment or more buyer. Most of these consumers, they’re coming in and your average 38 year old consumer today has been spending their savings over the past 10 or 15 years paying down their student loans, they still have some outstanding.
They’ve saved up a little bit of money to buy a place, but literally they’ve probably been renting for 15 years and they’ve been paying their rent on time and they’re wondering why they’re paying their landlord’s mortgage payments. So we’re helping them surface these first time home buyers programs where with as little as 3 or 5 or 7% down you can buy a house and use that as a vessel for savings and socioeconomic mobility so we’re able to find them and help them do that.
The other thing that we see, which is interesting, is your traditional mortgage process is built for someone who is a vice president at IBM (Peter laughs) and you know, has W2 income and a salaried job. We see consumers who are being paid…if they’re working at a major tech company they’re being paid in restricted stock units, and that’s something that other banks or mortgage companies allocate zero value to and we are able to actually by being able to digitally verify that, show that it’s consistent, directly interface with Fannie Mae and the like to provide you credit for that type of income; for the 1099 income, the RSU income or, you know, other types of income, small business income.
Our machine is able to help ingest that data, verify that data where every other mortgage player is saying, oh, this is complicated, I don’t want to deal with this. When you’re dealing with somebody who’s commissioned, they just want the easy loans, they want the loans to somebody buying a $2 million place and, you know, the person who’s buying a $300,000 place, that’s not what our engine does. Our engine treats everybody really well and our team of non-commissioned loan consultants, they’re there to help and empower the consumer to get the best outcome and the best house that they possibly can.
So we’re seeing a lot of that which that gets down to the last thing is that because we’ve taken all the stress and the brain damage out of the process, we can spend time educating these consumers. You know, the sort of homeownership myth in America used to be…well, everyone should buy a house and, you know, the credit crisis, post the credit crisis, people are worried that based on what happened with their parents or with their parents’ friends or others they have so many horror stories of someone who just bought a house they couldn’t afford. People want to buy a house, they really do, but they want to buy a house they can afford and so we can surface that and then actually carry through with that all the way through the process.
Peter: Okay, so on your website it says…we won’t rest until you can get a mortgage in one day at no cost. So I guess it brings up several questions. Obviously, the one day piece is fascinating. The last time I got a mortgage I think it was about a 60 day process for me and it was highly frustrating, I wish you guys were around back then. But anyway, I want to ask, how long does it take today and what needs to change to get to this 24-hour turnaround you talk about?
Vishal: So actually, we’re really proud to say that today in certain markets, I think six markets, in Seattle, in San Francisco, in Atlanta, in San Diego, LA and Denver, we can do a mortgage in one day. We can take you from going online on your mobile, getting pre-approved in three minutes, allowing us to pull some data from your employer and your taxes, locking a rate in 15 minutes, getting fully verified, underwritten and being eligible for our Better Offer process which basically gets you a commitment letter, turns you from a mortgage buyer into one that can waive their financing and appraisal contingency in one day.
Vishal: So that is live. Now regulatorily, we still need ten days to close because we have to issue some disclosures and those disclosures have a cooling off period, but that’s a sort of closing process, but we can give you total certainty and back it up with a guarantee such that if you were to waive your financing contingency and for whatever reason something falls through, we will back up your earnest money deposit with up to $50,000, we’ll reimburse you for that.
So we’re doing that in six markets. Those six markets are probably like 15% of American housing. We’re going to take that national, but we’re there. We’re at the beachhead, we’ve got to push through (Peter laughs) so we’re super proud that we’ve been able to make that happen.
Yes, that mortgage today is with zero fees and our best price guarantee where we guarantee we have the lowest price by at least $1,000 or we’ll pay you $1,000 so it comes with our Better Price Guarantee so no fees, Better Price Guarantee, one day mortgage, live today in six markets, national by end of 2018.
Peter: Okay, wow, so I take it if you’re doing one day, you’re not actually physically speaking or interacting in any way with the buyer? Is this all automated, obviously they’ve got to enter their data, they’ve got to give you some data, but how automated is the process?
Vishal: It’s as automated as you like it to be so you can do this without ever speaking to us, you can do this while speaking to us the whole time through so if you want to be on the phone the entire time this is all happening, that’s cool with us too. We generally like to talk to the consumers that we’re empowering with this tool, but yeah, effectively it can be done entirely automatically.
Vishal: There are some property types where, you know, the data may not be as clean or new developments, things like that which might require an onsite visit, but that happens all in one day.
Vishal: In each of these markets we have local appraisal panels and local property inspectors that can do, you know, all of the things that need to be done within a 24 hour period.
Peter: Wow, that’s impressive, that’s impressive. You said on a panel one time, I remember, that your rates can be or I don’t know if they are all the time, but they can be better than if you go to Chase or Citi directly. The rates that you offer can often be better, I mean, is that true and how is that possible?
Vishal: That is correct. We can give you a loan cheaper than Citibank can give you a loan using Citibank’s financing…
Peter: Right, okay.
Vishal: …which is crazy, right. That’s been the traditional challenge of fintech is that fintech companies are able to create a better customer experience, squeeze operational cost and make things cheaper, but fundamentally they’ve had a cost of capital disadvantage. By aggregating the demand for financing for all of these investors, including six of the seven largest banks, and by our…you know, one of the benefits of us taking over an existing mortgage bank and by having the direct interface with Fannie Mae where we’re a direct Fannie seller/servicer which is better than most of the banks in the country, we actually do not have a cost of capital disadvantage. We actually have a cost of capital advantage with respect to us versus 99% of the banks in this country.
Peter: That’s amazing. So then how are you making money? What’s your business model?
Visha; What we’ve been doing is…the way we make money is the investors compensate us for manufacturing a better mortgage at a cheaper rate which is great, right. So we are giving a cheaper rate to the consumer and so now that loan, by the fact that the rate itself is cheaper, has a lower default risk profile.
Peter: Right, right, yeah.
Vishal: And so we’re able to take a loan and actually get a premium for it by enabling a lower chance of default and by manufacturing it at a lower cost and we make that premium and that’s how we make money.
Peter: Right, okay, okay, interesting. So then we chatted a few months ago and I went back and looked at my notes from that call and you said at the time…you said we are building the Amazon of credit. So what do you mean…does this mean you’re going beyond the home mortgage, what do you mean by that?
Vishal: We believe the home process, the home ownership process…I mean, that’s a $30 trillion asset class where, you know, somewhere like 10 million consumers are either buying or refinancing a mortgage…the size of that is $2.5 trillion, and what we’ve done is we’ve done the hardest financial asset class first and we’ve made the process of getting approved for a mortgage like today’s process of getting a retail installment loan similar. Where we believe is that obviously if we can give you a mortgage which is the largest financial transaction that most people will ever undertake and we have your income statement, your balance sheet, your cash flow statement, we have all your preferences, all your spending data; we are able to easily decision you for any other asset relatively quickly.
So whether it’s insurance, we do title and homeowners and others as part of our process today, one click. You know, if we can get you a house, we can certainly…the next time you see a car, take a picture of the VIN number and we can decision you for that and that in one click. You want to build a new deck, take a picture of the deck at Home Depot and we will be able to get you that and add that to your mortgage rather than a 12% retail installment loan in one click and have that payment be tax deductible and increase the value of your home and lower your existing mortgage payment in which case it might cost you less than what you were thinking about. So all of this becomes possible once that mortgage becomes digitized.
Peter: Right, right, that makes sense. So we’re almost out of time, but I want to get, there’s something I’m very curious about, I mean, you touched on it a little bit earlier, but I want to talk about data and sort of the data sources that you’re using and how you’re…is your secret sauce having been able to get all this done so that you can verify this person, you know, in an automated fashion. Tell us about…like obviously you’re pulling in the traditional data sources which most lenders do, but I’m curious if there’s anything else that you’re doing on the data side to help kind of measure the risk or underwrite these customers?
Vishal: What we are creating and we again talk about the Amazon of credit, we’re creating an ecosystem where people are going through their largest financial transaction so we’re surfacing areas that they need further education on, we’re surfacing things that they can do to improve their financial life. One of the use cases of refinancing a mortgage is for debt consolidation or to buy something new. So by surfacing to the consumer effectively if they plan to pay all of their bills on time…hey, not only can you do this refinance and lower your rate, but actually we can refinance your student loans, we can refinance your auto loan, we can refinance all of these things and it’s just like one click, one click, one click and we can just show you.
If you do that and you take this 5 year asset and you turn it into a 30 year obligation this is what your monthly payment will be and how much money you’ll save. This is how much money you’ll save in interest by taking this 12% loan and turning it into a 4% cash out refi. All of that we’re able to do so we’re able to capture this data, but more importantly, we’re capturing the data and what others are taking and effectively sending only the sliver that an investor or securitization trust or a rating agency needs. We’re actually taking all of that data to add super rich context around the consumers’ personalization like personalized optimization and using that to optimize fundamentally the one thing that matters to the consumer which is the monthly payment…
Vishal: …and the cost of that. And so we’re building this super rich data ecosystem that then we can utilize for all of these other things.
Peter: That makes sense. So last question, I can hear in your voice how passionate you are about this process and it’s quite impressive what you have been able to get done to date, but I’m curious about what you are working on personally today that most excites you.
Vishal: So the thing that excites me the most is to be able to turn any consumer into a cash buyer. For me that’s like…three years ago, I lost the place we wanted to live in and raise our children in to an all cash buyer. I want to be able to take any American consumer who can qualify and be able to turn them into a cash buyer in one day so they can get and buy the house of their dreams, raise their family, improve their socioeconomic status, be able to use that house to send their kids to college and pay for their retirement. I think that’s super, super empowering.
Vishal: Super empowering and it’s like basically would be the most amazing thing that I could end like my fintech career with.
Peter: It is a noble endeavor, that’s for sure. Much more to talk about, but we’re going to have to leave it there, Vishal. I really appreciate you coming on the show today.
Vishal: Thank you so much, Peter, really appreciate you having me.
Peter: My pleasure, see you.
Peter: Wow, I don’t know about you, but I thought that was quite something, pretty amazing. They’ve been able to take a 60 day process down to one day and I think the reality is banks offering mortgages in the way that was done in the 1990s and 1980s, those days are numbered. I actually think it will be literally impossible to obtain a mortgage in…I don’t know whether it’s five or ten years time, I’d say definitely ten years. It will be impossible to obtain a mortgage that takes 60 days, every mortgage will take less than seven days I think. You’re going to see companies like Better…they’re changing the expectations.
People go into buying a house expecting it to be painful. As companies like Better get bigger and more well known and others enter this space and do things in a similar way, it’s going to become a totally different market and I think it will encourage actually more people to buy homes. As Vishal said, they’re able to buy better homes that they can afford because they’re getting a more efficient process that clearly is not going to cost $8200, or whatever he said, it’s going cost in probably the low three digits, maybe even less, when it all comes down to it so it’s going to become a much more efficient process.
Anyway on that note, I will sign off. I very much appreciate your listening and I will catch you next time. Bye.
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