Why the Right Eviction Rate Isn't Zero w/ Brendan from Findigs

Welcome And Guest Introduction

Eli Wachs 0:20

Thank you so much for joining us on this episode of Risk and Reason. I really appreciate you coming on. You've had an exciting uh past two months or so. And I I feel we'll we'll try to loop in Mount Everest and uh the world of tenant screening. But why don't you introduce yourself, tell us what you do today, and thanks again for coming on.

Brendan 0:39

Yeah, absolutely. It's great to be here. Uh so I'm Brendan. I'm a director of product at a company called Findiggs that does uh tenant screening. So think about reducing fraud and uh getting to approvals as fast as possible. Um have you know way back an engineering background, um, started at a hedge fund, so nothing in the physical world. Um, and then went into mortgage startup, better. Maybe we should talk about risk there because see a company go from $0 to $7 billion back to near $0, also fun. Um, and then moved into the rental space with the same kind of focus.

From Engineering To Product Thinking

Eli Wachs 1:15

Yeah, let's maybe go from uh moving from hedge fund to better. Uh, because that that is still going from you know corporate world per se to uh startup ye, if if you want to give me that. And I believe you're working around underwriting there. Uh could you maybe talk me through kind of like what got you excited to join better and then what you uh what that was like redefining how we maybe think about capital markets and underwriting in the home world?

Brendan 1:40

Yeah. Um it was really because I hated being an engineer. Like I I figured out that I like solving problems. And you studied engineering. Studied engineering, well, uh, you know, industrial and systems engineering, which the it was called IE, which people would call imaginary engineering. Can't build a bridge, can't build IKEA furniture. Not but I liked you know building systems of things. Um and so, you know, I I went to do that with code because I thought, you know, what is the fastest way to solve problems? And it was when I was deciding what my major was, it was 2014. And at that time it was said, you know, go get a coding degree. Yeah. Um and so I was like, okay, cool, I'll go be an engineer, and that's how you solve problems at scale. Um and I found that that's not actually true. It's the people that tell the coders what code to actually write are the people that solve problems at scale, not any disk coders. But I would found myself, you know, writing a bunch of code, having a bunch of meetings about code, and then not really seeing how it affected anyone. Um and so I was like, can I go a level up in figuring out what what are the systems that we should even design to affect some outcome in the real world? Yep. Um, startups are a great place to do that because you are taking a bunch of ambiguity and organizing it into a system that then, with you know, engineers, can run on its own. Um, and that was really the dream of Better is to say, you know, can you do that with mortgage, which is incredibly complicated, has a lot of digital and real life components that are interacting, reams and reams of paperwork, um, but is a well-defined process. Like there are rules that you follow, there are if-thens, then that. Um and so I was really interested, can you get, you know, person input on the left side and then a machine that runs and it spits out, hey, now you have a house on the the other side. Um and that problem really, really attracted me.

Eli Wachs 3:34

What now it's an interesting space in that we've seen different space, but when we just think about home buying, uh open door uh has become was this fascinating spec, almost zero, now one of the hotter stocks out there. What do you think people maybe got wrong about housing market uh uh like as it intersects with technology? I guess either from this underrating standpoint, this risk standpoint, why did it get all from better open door kind of this attraction in maybe kind of like that 2015 to 2020 time frame?

Why Mortgage Tech Is So Hard

Brendan 4:04

Yeah, that's a good question. I mean, the cynical point in me is like that's rates. That's you know, when you have 2020 was the best year for better ever because it was the one quarter of profitability when rates were at zero and anyone wanted to buy mortgages. So that's that's maybe when it's easier to do well. Um but I think that's a cop-out answer. I think um the answer is it's hard. Digital products are relatively easy to do with SaaS. Not easy, but you are solving a problem that exists entirely in the digital world. And so if you go, like if you look at mortgage, you know, people go online to find a home, they're creating a product that lives entirely on the internet, which is a mortgage, um, which is why for refinance it was actually super easy. That's where Better made most of its money in 2020 because it is almost entirely a digitally lived product. Then you start putting in things that have to happen in the real world around that, of like you have to have someone um that assesses the value of the collateral, which is your house, right? You have to have an inspection. All of these things have to happen in order. You have to have signings that in a lot of states have to happen in person. As soon as you're making this Rube Goldberg machine that is partially digital and then partially in person, all of the really good designs of, oh, we have, you know, this email that goes out and then oh, we'll put it on the blockchain or whatever was the big thing then. I remember mortgages on the blockchain very fast. I never knew why we were putting them there, how we were Well the funny thing is like it's obviously better to do something like that because the alternative is you have mortgage custodians that have literal like an actual mortgage is a stack of like 500 pieces of paper, right? Um that can be digitally represented. But if you put it on the blockchain, you have to have some way of getting that physical stack of paper onto whatever digital representation that you want. And I think a lot of the Silicon Valley is for Solana. Yeah. The Silicon Valley hubris is like if there is a digitization path, then we can make this abstract machine that does it. And um, if you get soft bank to believe you, you can get a lot of money to do that and potentially fail at it. Trevor Burrus, Jr. Sure.

Eli Wachs 6:08

We when we think about I guess uh risk, maybe historically go back to uh like KYC kind of comes from the Patriot Act, and and there's this governed thought of we need to regulate our banks to make sure they're not letting uh uh terrorist networks or cartels use our rails. That's where kind of people think about this phase. Uh homes, uh apartments, they're not necessarily come at that from a regulatory standpoint. They they come at it from a these are very valuable assets that we are figuring out if you have the ability to pay. And if we give it to you, could you maybe talk about when you think about this starting with them like what actually goes into underwriting when you're thinking about that and when you're bringing this digitally? And then we'll get into more of your current role.

Brendan 6:49

Yeah, absolutely. So yeah, it's it's it's not even about uh if you think about it from the the government perspective, which is like keep bad people out because they will do a bad thing. It's more like fairness. Is yeah, so it's it's almost not even fairness. It is uh when you create something like a lease or a mortgage or any kind of uh bond or lending someone money on a credit card, what you're actually creating is an asset, right? So it's going to give you some cash flow uh because they will pay monthly or at different times, and that has a risk of going away. It has a risk of being zero. Mathematically, what you're trying to do is create a process that gives you the best mean and standard deviation for that asset, right? And so that all boils down to math. Um and so you know, if if there are negative side effects of that from the asset perspective, you could really care less. Right? You want a well-performing asset. Now it just so happens that all of the tools that the government uses to, you know, keep terrorists out are also useful to detect if someone is highly likely to not pay back whatever this bond is or this uh loan is, uh that is, you know, whether you get the money on your asset. And so I think maybe underwriting is probably older than a lot of the security stuff, uh, the applications. Um because you are really trying to minimize the variance of what those payments are. Um and we can go and talk about like what is the right amount of not getting paid back, like what is the right amount of defaults. Um because it's not zero, right? It's not zero. And you know, working with property managers who who are making these assets called leases, they are in the mindset that it should be zero. And can you explain maybe why?

Eli Wachs 8:34

Because it's counterintuitive, but this is Yeah.

Underwriting As Cash Flow Math

Brendan 8:36

Yeah. So this is probably the most important thing of um you have to make some guesses about what kind of situations and people and uh amounts that you make these loans to. So for mortgages, this is the inputs are like credit score, loan amount, the ratio of the loan to the value of the house. Uh for leases, also similar credit score, income, um, the rent of the apartment, maybe even some uh interesting stuff like the floor of the apartment or whether they have a pet or not. But all of these are inputs to a machine that tells you how likely someone is to pay back. Um and it's not perfect, right? And so you have to set some cutoffs that are above this line, we will rent to this person or we will give this mortgage, and below this line, we will not. If you did the math and you said we're going to set those standards so high that no one breaks a lease or no one fails to pay back a mortgage, you would be making very, very few mortgages, right? You would be making very few leases. Um, because it would be only the absolute most credit worthy people who have a ton of money in the bank. Um, and maybe 95% of the people in the tier below that will pay back their mortgage, uh, it's worth it to go make those loans. And so saying to property managers, you know, hey, the right amount of evictions is not zero, they go white in the face and they're like, what are you talking about? Like, why are you putting people in my units who I'm going to have to evict later? Yep. Um because it's costly to evict to actually do the thing or what does that process look like? I feel like people varies by state. Um but uh and and the states are on kind of a spectrum of uh how hard and easy they make it.

Eli Wachs 10:19

Uh episodes of uh squatter strides and uh they can't kick them out.

Brendan 10:22

California's kind of wild, Alabama's a little bit easier. Um so you can imagine the spectrum, the access that that uh uh does it on. But it's it is both the number of days of lost rent that you would get and the the legal costs of the eviction. And so in places that have you know high tenants rates, it's longer number of days that you're not gonna collect rent and longer uh legal process, which would mean more legal fees. And so if you think about um, you know, we're we're like a mortgage bond is saying, how many of these months am I going to get paid back? Uh are they going to prepay it? A lease is saying I have this uh this unit, this apartment, how many days out of the year am I going to be collecting rent on that? And so as soon as someone stops paying, it's that amount of time plus the amount of time it takes to evict them, plus the amount of time it takes to fill it again. And so they really want that to be zero.

Eli Wachs 11:15

And I guess to overly simplify the formula that you're playing with, it's kind of uh amount of occupancy times uh like likelihood to pay. So in the perfect world, it's a hundred percent occupancy, zero percent default, but you'd rather probably be at a hundred percent occupancy and one percent default than ninety five and zero.

Brendan 11:34

This is really interesting. Different property managers will run their assets different ways. So I have seen both the like we want to keep 99.9% occupancy and take flyers on lower credit people, or saying we are fine at 95% occupancy and we want to deal with zero evictions. And a lot of factors go in there that's like, what's your average rent? How long does it take to get someone out and get that paying again? Do you have a risk layoff product like a uh there's this product called a rent guarantee bond that if someone stops paying, the insurance will make you whole on that? Um and so there's all these tools that go back to that same objective function that's like, how many days out of the year can I collect rent on this unit?

Eli Wachs 12:15

Yeah. Now I guess enter fund eggs. Uh do do are these things that you think about of kind of can we vertically uh integrate the these types of elements of not just the risk underwriting, but if we feel very confident, uh the insurance or helping kind of give advice of, you know, this is actually what we're seeing from a pricing perspective. So if you're here, we can probably get 95 up to 97 without lowering your threshold.

Brendan 12:37

Yeah, absolutely. Um so I'll go kind of back to the start on findings. You know, uh it started as kind of this blob of information that uh we gave to property managers to say, we're gonna co-locate someone's credit report and the information about their income documents and fraud signals and all these things. Um, and you can bring whatever your workflow is that to make a decision, right? And I think one of the first things that we did that was new in market was uh integrate plaid for bank linking. And so it's kind of this like uh second party verification of the income that someone has instead of you know writing up bank statements or pay stubs and wondering if those are fraudulent. And so that you can see is maybe on the occupancy axis, it gives you a little bit more speed, which means you can fill those units faster. Maybe if you fill it a day faster on average, you know, that's one 360 fifth more rent that you're collecting. Um and then on the eviction axis, on the the, you know, how much risk you're taking on, you can detect fraud more, which lets you get more people in who are not going to um be evicted. Uh as that evolved, it it's almost like screening companies are becoming a Swiss army knife of those tools. So like plaid being the first one, but then there are all of these tools to detect fraud with someone's device data, detect fraud on um documentation that they may upload, um, check their backgrounds, uh, check the last place they lived, did they pay rent there? Um so all of these things that are like predictors of if they are going to pay rent. Um at some point you get to information bloat, right?

Eli Wachs 14:17

And if you're providing uh Especially for a PM who's used to, as you're saying before Fondigs, having very little information.

Evictions, Occupancy, And Real Costs

Brendan 14:23

Right. And and this statistic is crazy. Um the average turnover for leasing agents at property managers is about 50% per year. Wow. And I tell that to some property managers and they go, Oh, phew, I thought it was it was just us. We're actually a little bit above that. So I think it may actually be underreported. Yeah. Um, but that means you can't institutionalize a lot of this knowledge. Uh-huh. And the more complex that it gets, the more you need some like external institutional knowledge. Um, and so that's where we came in with uh a new product called decision assist. And that is us saying, okay, let's start you out at some thresholds. Let's give our best practices on all of this uh this data around fraud and um underwriting risk. And then we will automate what we can around that because almost all of this exists in some form of structured data. And along with all of the rules that make you uh you know have to treat every single applicant the same and all of the fair credit, fair housing laws, um, it's really beneficial to have some kind of automated process that does this. And so what we have is we go through all of that information, bubble it up to what we would call like insights. So that's maybe a score or something, or looking at their credit report or their background reports, um, and then implement those decisions. And so the things that you get out of that is we should be catching fraud more often because we have all the tools and we know how to use them. And so reduce that, you know, number of uh delinquent payments that you get. Um and if you do it faster, uh then you should be filling your unit sooner. Uh one thing that we recently found out on that is if you are giving a decision to someone who applied to an apartment within 12 hours, you get a six percentage point boost to the conversion between approving them and them actually signing a list. So if you imagine that from your side, you're like, I'm looking for an apartment, you're maybe applying to three, four places in New York, 10, 12. Yeah, you have to do it really quick. Imagine if you applied and then, you know, two hours later you get back an approval, you're likely to stop shopping then. Yep. And so what we've seen is like speed is really, really important. And the the controversial thing that I'm like thinking about is how much does that compare to letting more fraudulent apps through on the overall objective function of collecting more rent? Um and that would be up to that objective function of all of those things around eviction.

Eli Wachs 16:53

Yeah. Now walk us through, you know, i leading it kind of being director of product. What when how do you think about I guess uh when you're building that new module about Preth versus depth? So how do you think about this trade-off from a risk standpoint, but also more broadly of when do we actually need to add more specific point solutions or something in a specific area versus we want to tackle on a completely new product line?

Brendan 17:17

Yeah, that's that's interesting because you you can go in the integrated route, like you mentioned, of integrating these rental insurance bonds or you know, the ability to pay your security deposit over time, or all of these cool things that um change conversion around the edges, pets verification, which we have. Um versus it's like a sneakily huge uh area that uh Oh yeah. I mean, people's pet very with ESA letters proliferating. That's another form of risk of like you're like, oh, it's a pit bull, which we don't allow, but it's an ESA pit bull, emotional support animal pit bull. And you have to be like, is is that letter really real?

Eli Wachs 17:53

What's the uh most and I'm sorry, I totally cut off your question, went back to, but what's the most niche support animal that you've seen applied with?

Brendan 18:00

Oh it was um it was some kind of lizard. I think it was a gecko. Yeah. So it it's funny, like there's three levels of animal that we classify as like household pet, which is just anything. Emotional support animal, which is like a therapist or psychiatrist or something, has to write a letter, you have to get them certified, but it's kind of wishy-washy.

Eli Wachs 18:18

Yeah.

Brendan 18:19

And then service animal.

Eli Wachs 18:20

Yeah.

Brendan 18:20

And service animal is like you can't ask any questions about it, it's helping a blind person, or it you know, does alerting on your blood sugar. Uh service animals, interestingly enough, there's only two types of animals they are allowed to be. One is a dog. Do you know the other one? I'm gonna give a horse. It is a miniature pony. Wow, let's go. And we have we have seen some. Like we've we've seen it all. I working that. Yeah. Uh and what job does the miniature pony do?

Eli Wachs 18:45

Can you bring that to a New York City apartment or probably not.

Brendan 18:48

Okay. There's probably more single-family homes.

Eli Wachs 18:51

Yeah, that's what I was thinking. Yeah.

Brendan 18:53

I also don't know how it does whatever job that you're like, it's a seeing eye pony or something. Yeah. Yeah. Um Yeah, we will we will have to see what they're doing.

Eli Wachs 19:04

Um, and it has a legal requirement, I guess. My final question, though. So if somebody applies with an emotional support pony, it the the single family home, they have to find a way to validate that. Yeah. Is that an FHA thing if not?

Brendan 19:18

Uh Americans with Disabilities Act. Okay. Um it governs a lot of the service animals, and then HUD obviously has guidelines around what you can ask. And the HUD guidelines are literally if someone says it's a service animal, you ask, hey, does it perform a service for you? And if they say yes, uh and you ask if it's a dog or a pony. Yep. You really shouldn't ask more than that. Yeah. Which is interesting. And they're real teeth to the regulations that you're dealing with. No pun intended. Yeah. Um Yeah, real teeth to the regulations, um, maybe less so in the next three years. Okay. Uh, because CFPB is a lot of the ways that like consumer fairness uh gets um action. Yeah. Yeah. Uh and less less desire for enforcement. Yeah. But um, you know, statute of limitations on these things are more than one administration.

Eli Wachs 20:05

And can you maybe just give like a sense of like how how large of a fine could a PM actually get if they were found violating one of these?

Brendan 20:11

So yeah, it really depends on the the how many people it affects, but like you can get into the class world where it is a class action lawsuit of like one person doesn't like that they have been declined for an apartment and they throw a Hail Mary because they maybe know don't know you're doing any kind of discriminatory practice. Yep. But then an auditor is going to go look at every decision that you made. There's a cost. Yeah. And if you there's a cost there of just doing the investigation. But then if it's like, yeah, you didn't train your leasing agents well enough to maybe not open the ID picture first, and they could have been taking race into account, then like every person who's not white who applied to your apartment now can be looking at joining um uh joining action a lawsuit against you. Um and so PMs really, really want to avoid that.

Eli Wachs 20:58

Yeah. Okay, so I I apologize. We'll get back to it. Breath versus depth.

Brendan 21:03

Yeah. Um you really think about what is the marginally next important thing that is going to improve uh so we we've been kind of dancing around what the overall objective function is. There's this acronym called NOI, net operating income, uh, that a lot of property managers use. That it's like, hey, it's all the rent and the revenue that you collect minus your operating expenses. Yep. Um and so you know, the language that they talk in is either you are reducing some of those expenses, uh, of which our software is one, right? Yep. Um, or screening applications is one, or paying your leasing agents to do showing, um, or you are increasing the amount of revenue that you can do. Um if you break down that tree a little bit further, you can increase your rent price, which is a space that we don't play in, um, but we can talk about you know some of the cartel action that's been going on there. Um big lawsuits. Um

Eli Wachs 22:00

Which got settled, I believe, recently.

Brendan 22:02

Yeah, I'm I'm not sure. Um they they keep popping up because they'll like be in little state actions and then rolled in. But um real real page is the company there um that does some it's like algorithmic suggestions of what your rent prices would be. We don't really play in that space. And after seeing that, you know, a little bit less excited too. Um but saying maybe you have figured out the market clearing price for your rent, given that, how do you fill uh your units uh most appropriately? And so figuring out is whatever we're about to build going to reduce more fraud? Well, how much are we catching of the total? There is no way to know of the total, but you can guess how much you're catching.

Eli Wachs 22:42

Um such for proving a counterfactual from an ROI standpoint.

Brendan 22:45

Yes. There is when when someone when you um kind of naively say, like, what percent of fraud are you catching? Completely ridiculous question. It's an impossible question it is an impossible question because you did you just don't know the good ones that are getting through.

Eli Wachs 22:58

It's not like you block them and they email you, hey, just an email. I I was never planning on paying that back.

Brendan 23:04

Yeah, you observe the ones that actually do that, um, but you you don't really know the total. And there was the the CEO of Graystar, which is a big, big multifamily operator, was saying up to 50% of the applications they get in Atlanta are fraudulent. It's like, I don't really know how you got that, but based on what we are seeing in the data, totally could be true.

Eli Wachs 23:25

Aaron Powell Atlanta is a statistically anomalous city of fraud. I think so much payments flows through there, but yeah, it's fascinating for us.

Brendan 23:32

It is it is my hometown. It is uh it is a hustle city, and that extends to doing fraud. Uh yeah, but it's it's you know, what is the marginal amount of fraud that you think you can catch? What is the marginal speed that you think you can put on there, or what is the marginal amount of uh declines or people who don't actually sign a lease that you can turn into leases? Yeah. Um and so uh property manager will sometimes talk in terms of net leases on that revenue side of the equation, say, like, does this get me a net lease? Yeah. So if you're looking at something like um, can we make the application decision process two hours faster? Well, if you are at 72 hours on your average time, two hours probably doesn't do that much. Um if you're at 24 hours, two hours starting to have an impact. And if you're at six hours, you might be so far ahead of anyone else that two hours also doesn't matter again.

Eli Wachs 24:24

Yeah, it's like a barbell.

Brendan 24:25

Um if you're at a new product that you're like, could I have uh applicants pay for this insurance product that allows me to approve them even if they don't meet my credit standards because I know I'll be covered if they don't um actually rent from or if they don't pay the rent. That's gonna turn some declines into approvals, which is gonna turn some approvals into leases, which means you're gonna get net leases. Uh it's gonna put some friction in the process, but you can say, like, here is the marginal chunk of declines we expect to now be living in our apartments and paying rents.

Eli Wachs 24:57

Yep.

Brendan 24:57

Um and so it is figuring out what is the chunkiest thing to do there.

Eli Wachs 25:02

Yep. I want to talk about from a regulatory standpoint, they're even if right now we're maybe not in an age of great enforcement, it's still very much there. And a lot in the space, fair housing, uh, you know, you need very um concrete binary policies in a way. When you think about increase of AI tools to maybe try to combat fraud, uh these can be good, but they're also black boxes in many ways. How do you think about managing that uh when you're evaluating a tool?

Product Strategy Through The NOI Lens

Brendan 25:29

Uh strong thoughts on AI. Um and so every every tech company, especially like B2B SaaS platforms that you see is gonna have AI on their website. Of course. Because you you kind of have to this way. Is the is the hot new thing. And I am saying that knowing that AI is on the front page of FindEx website too, right? Um I think there are good versions and bad versions of using AI. If you have AI doing any decision making, what you would call like, you know, trying to put in inputs, stirred up with a magic chat GPT wand, and get an output that is like, yes, we should or should not uh rent to this person. Terrible idea. It is not going to be compliant because it is not deterministic, so you can get different answers if you run the exact same inputs multiple times. Um there are it is really hard to guardrail it. Um and regulators really do not like it. Um and so some companies that are doing you know, even communication with applicants in different ways. Uh there's there's two kind of things that you see in feedback from property managers. One is there's so many guardrails on this, it can barely do its job. It's not even usable. It's not even usable. Or it is so unpredictable that it's not usable. And I think we have yet to find the sweet spot on that, even letting it close to decisions. However, where it is really, really useful is if there is a task that you could teach a reasonably smart human to do in the course of an hour or two. So, like, hey, read this pay stub and figure out what the net pay is, what the pay period start date is, what the pay period end date is, and then calculate a pay amount for that. Absolutely, AI can do that, and we are starting to use it in tons and tons of ways that make all of this much, much faster. If there's things like the metadata on this document uh should you know meet these somewhat subjective categorizations, um, can you look at it and categorize it uh to see if it could potentially be fraudulent and flag it for human review? Does it really, really fast, does it really reliably? Um one of the things that we one of the very first things we put it on was actually a net improvement over the humans that we had doing it. So it was uh on a credit report, you have trade lines or collections, so it's you know one open account that you have. And if that gets, if you don't pay it and it gets sent to a collection company, uh on the credit report, the the only information that someone will see on there is like the creditor is progressive or Verizon. So you didn't pay your phone bill. There's like $87 in Verizon collections there. Um what we do is set some thresholds around how much collections are allowable and some someone's credit report report before you decline them. But those are in broad categories like phone and internet bills or utilities or a previous landlord collection or credit cards. Um if you have operators, especially offshore, and it just says progressive on there, you and I know flow from progressive, that's insurance, right?

Eli Wachs 28:35

Of course.

Brendan 28:36

They don't. Um but you know who does because they have all of the internet is ChatGPT. Of course. And so if you do a categorization exercise that is just like the task is so atomic that you do the collection grantor, the credit grantor is progressive, please categorize this. AI is going to do it faster and better than a lot of operators. Interesting. Um and then if you make sure that uh you kind of define everything as a function that is very, very easy to see the input and the output, you're not running into this um discretionary zone with AI that I think a lot of people get tripped up in.

Eli Wachs 29:11

When you take into account, I guess, AI, but more broadly just recommendation that you guys are bringing to the scene five years from now, what do you think are the biggest changes in the tenant screening industry?

AI That Helps Without Breaking Compliance

Brendan 29:22

Yeah, that's interesting. I think um kind of opening it up as a marketplace where the renter or the person looking to rent has more of the power in that relationship. And as a person who sells to PMs, you know, hard to hard to you know advertise with that. But uh, you know, if you could imagine if you could imagine one place where every time you go look for an apartment, so like New York it's street easy, right? But imagine you had a street easy profile that just had all of the last application that you made for an apartment saved, right? Yeah. Um like a passport. Passport. So like you have a profile. Uh and you know, we verify, so this is fine, it's not street easy because you know, competitor at some point. We verify all this information about you. Uh you maybe apply, you get into an apartment. A year later, you're looking for another apartment in New York. Maybe in other places you're staying a little bit longer. Yeah. Um we already know a lot about you. We can just confirm that's like, here are all of the places that you're already kind of qualified for. And then um if you want to live somewhere and it is, you know, $2,000 a month, a lot of PMs would rather you say, Hey, could I take that for $1,900 a month than not apply at all? And so there's almost this uh bringing in the other side to make it a two-way market by saying, Hey, renter, here's everything you're qualified for based on what we know about you. Here's an easy apply button that will go right into where these uh property managers want and tell us what you want so we can tell them what you want. So it's less of the PM's just like setting a price and more finding a market clearing price for wherever you want to live. And then there's all the things of like the mortgage off ramp from that. You know, if you want to now transition to uh, you know, buying a place, well, it's all the same information that you were using to rent a place. Yeah. And we have, you know, this history of you paying rent on time, which mortgage providers uh can now use as positive credit information. So Fanny and Freddie um added that relatively recently within the past five years. Um and so making this like really seamless, hey, you tell us about you, and we can help with your entire like it's more than home ownership and renting, it's where you're living journey in a way that you know I think a bunch of companies have tried to do. That's really cool. Yeah.

Eli Wachs 31:51

Maybe uh then kind of like off that. Um if there is one thing that you don't think will happen, but you really wish it did. So I guess the other way of thinking about this is what's something that today you wish more PMs took seriously, or you wish more people actually leveraged for this to be better experienced.

Brendan 32:11

Hmm. That's an interesting question. Um it's a really, really small thing it is not a big thinking thing. It's very small vendetta. But the idea of personal guarantors.

Eli Wachs 32:23

Hmm.

The Future Marketplace And Ending Guarantors

Brendan 32:24

Huge industry really makes me mad. Um personal guarantors, so this is this is, you know, maybe you don't make enough money, or the proof of income that you're using is an offer letter, or your credit's a little bit lower than the standard. A lot of property managers will let you say, give a co-signer or a personal guarantor. And it's like your parents or or someone uh who makes a decent amount of money, and they like guarantee your um lease a little bit if you don't pay. Stupid process. Because I could be making $10 and have a $500 credit score, and a lot of these property managers have set up rules that say, well, if you get really anyone, or maybe someone in-state, or maybe it has to be related to you, to kind of vouch for you, yeah, you can live here. And it's like And are they verifying the income of the guarantor? They're verifying the income of the guarantor, but it's usually something like, oh, we'll subtract out your mortgage and then you have to have enough income to pay the rent, or you have to make, you know, 5x the monthly rent, so you're covering yours and someone else's. If the person skips out on you and you can't find them, there is no way that you're finding their guarantor. And it's an entire other application that you have to do. You have to verify their rent, you have to pull their credit report, you have to pull their background reports, et cetera. Um for not that much. Yeah, what percent of applicants have a guarantor? It really depends. So, like college towns will have a lot. Um, it really depends on how permissive the property manager is. Some say no personal guarantors at all, we don't want to deal with it, it's impossible to collect from them. Uh some are like everyone has to have a guantor because this is a student housing thing. Yeah. Um it is a terrible risk transfer because you are paying a lot in time and money to get this thing that doesn't actually reduce your risk that much. Whereas like a rent guarantee bond is a literal contract that says if this person doesn't pay, then this bond will pay out, right? And it's usually like a lump sum that you pay up front. If you have a personal guarantor who's willing to help you out, just pay that first, you know? Yep. Um and so I really hope personal guarantors kind of die. Yeah. And we get a mathematically backed like insurance solution to this that makes sense. PMs are even going so far as to like do this on their own that if you see something like a credit risk fee, or they'll they'll like internalize this and try and write their own rent guarantee insurance just because they don't like guarantors that much. Yeah.

Eli Wachs 34:49

Oh, well, this is a big vendetta podcast. So we appreciate we appreciate you sharing it probably very close to around. Thank you so much for coming on. This was super insightful.