Today's guest is Pat O'Meara, Founder, Chairman, and CEO of Inveniam, a startup that provides data integrity and price discovery for infrequently traded assets including commercial real estate. We discuss why bad data leads to mispriced assets in private markets, how the company's software is unlocking trapped capital for major firms like Kushman and Wakefield and CBRE, and how the company uses blockchain to create a verifiable audit trail for every data point. Please enjoy this conversation with Pat O'Meara.
Jared Klee: Hey, Pat. Where I wanted to start this conversation, even before we get to what Inveniam does, which I'm hugely excited to start to dive into.
Before that, I wanted to talk about the problems of private markets. Cuz I think it's helpful to start with why does Inveniam exist? What is the state of the world today?
I expect we're gonna go deeper and deeper on this in a couple of questions. But let's start with, you've got this vision for private data. Private market data needs to get up, or at least as close to possible, the standards of what we expect in public market data. And we are so far away from that today.
Help me understand, like, what is this state of private market data today? If I'm dealing with real estate, if I'm dealing with private equity, if I'm dealing in the world that Inveniam deals with.
Pat O'Meara: When we think about public markets, right, we think about referenceable data that if the referenceable data's wrong, there's teeth in it. So somebody puts in, they file bad information, there's criminal consequence to it. And then a ton of people chew through that data, the publicly available data and that drives the ability for data rich high frequency trading, where the data's all referencable and you see massive trading in those assets, right?
In the private markets, what you see is a lack of consequence for bad data. You see data aggregated with intermediaries that are Oracles that you have to pay to access that data. Or someone is using that for their own book. People are spending literally hundreds of millions of dollars, aggregating data around a market that they're a dominant player in and they share it with no one. And what they do is they use that data asymmetry to extract massive rents from those markets.
And so while private equity, mez players, venture, private credit funds, there's a lot of money in there, but also the yield return that is expected by the best LPs is meaningful - double digits, low twenties, mid teens. They want real returns. And the person who's giving that up is the small business owner and those private equity assets.
What happens is those large funds come in, they fix problems, they elevate operationally, but in some cases they're just an aggregator and they're an oracle or a good housekeeping seal of approval that the data is what it is and there's an immediate pop in multiple.
What Inveniam is doing is we're taking this data where every asset is unique. And if I wanna buy a building, I put in a bid, I do 120 days of due diligence at the end of that process. You know, we compare here's the data that we thought, here's the data that we found, you know on the state of that asset and then we clear the trade.
That difficulty in accessing data real time, the difficulty in evaluating that data, creating comparison sets creates massive inefficiencies in this. And that's what Inveniam's trying to solve because there's not a yield curve between private and public markets. There's a yield cliff. And that yield cliff is people say, oh, I want a premium for illiquidity, right?
The way they achieve the premium is going after markets where they can arb into geographic sector, but more specifically, data arbitrage between public markets, get it there, aggregate a bunch, float em to the really most liquid part of the high end PE market. And suddenly they get us there.
But in Inveniam we're saying: how do we for those data rich, low frequency trading assets, how do we credential that data real time so we can prove the state of an asset any minute of the day, so we can prove the value of that asset, so we can then trade the capital stack. But the big problem between public and private markets is access to data, trust in data.
Jared Klee: You're talking about like I live in Brooklyn and there's any number of small shops all along here, many of which are brilliant businesses. But if I imagine like trying to go in and acquire those things first off, unless they keep good books and records, I probably don't trust them. Many of them don't, they're mom and pop shops.
But then I'm relying on some third party to come in and validate and revalidate and revalidate. That might just be for the accounting. If I then want to go understand inventory, I'm probably talking to somebody else. If I want to go understand the legal exposures and whatever else it is about zoning. I'm probably talking about somebody else. It's a gazillion different parties.
If I'm able to build up that view of the data, I likely have an information asymmetry where I'm going to take advantage of. They're effectively going to be the loser on the other side, cuz I have a better understanding of value than they do. Heaven forbid that someone then wants to buy that from me. They're either stuck doing the same due diligence that I just did, or they're stuck basically taking the wrong end of a trade.
Pat O'Meara: Or you have such a good brand name that your good housekeeping seal of approval credentials the data and that benefit inures to you, instead of the entrepreneur created the business. And this applies to every piece of the capital stack. Big banks, big private equity funds, small family offices. The value asymmetry in distribution is going to the person who understands that unique segment.
If we're gonna see private markets trade like public markets, we either need to create the world's largest database in the center that everybody references, which is a fool's errand. Or we need mechanisms to credential data in the asset owner's own systems real time.
How can we come to trust it? How can we do that? And then we can have financial instruments, so that suddenly have real time surveillance into that asset. And that real time surveillance can be everything from foot traffic. Elevator maintenance lease payments.
But as we become more and more atomic things like the Big Short, where servicers were creating a buffer 150 to 360 day buffer where you weren't seeing the real performance of the assets for, for sometimes months or even years into the future.
But here's real time data. I can see that real time data. I can manage my risk. I can price that risk. We're changing fundamentally the architecture about how big corporations think about data.
Many big corporations, the CEOs, their data strategy is get all the data in my data lake. I just need all the data so that I can process it. Snowflake took half a step and said, no, no, no, no, you can rent it, put it in a marketplace, make copies and put that for the referenceable datasets. But we're saying that's a half step. The whole step is you don't need any data in your database, other than that, which you've manipulated and improved on your own.
But your client's data, trying to get your client's data into your data systems for big entities, Kushman and Wakefield, JLL, et cetera. You're always gonna fail by definition. You move the data, you change the data, you're wondering is it up to date.
But if we can make every building, every private market asset, every infrastructure asset, every private credit asset have their own LinkedIn page where they're maintaining their own assets, data cuz they're economically incented to do so and they credential it real time and it's indexed so it can be found.
But right now, if you index data with Google, you've lost control of it. So if it could be found, you've lost control of it. We allow you to index the data so somebody can see. But have no access to the underlying data. And what we're doing is we're allowing you to control your own data, credential your data. And then if somebody wants to see it, you don't send them a copy of the data. Which is kind of how we currently think about it: send me the docs and it's a user centric environment. What we're doing is we're creating a data centric environment. So if there's 30 parties looking at a single building, they're all looking at the same piece of the data, the same leaf on the tree.
And if that leaf becomes disconnected, everybody knows immediately. This is no longer a live document, it's been altered. And what's the new leaf on the tree. What's the new golden copy of that documentation. And the asset owner is incented to credential their data real time cuz as you do that, you get more bids on lenders. You get more bids on equities, you get all sorts of better accounting treatment, regulatory capital release, all of these things.
Jared Klee: So it's the same reason that somebody, if you were gonna go set up a deal, the same reason someone's actually putting in the effort to dump stuff into a data room and keep it up to date. Basically, I know that I'm going to get paid more by doing so. You're creating a better mechanism.
First off, the data isn't getting moved. So we don't have the transformation, is it up to date problem. But secondly, I think we're gonna get to blockchain here in a second, you have it effectively an audit trail, the provenance of that data, demonstration of who it came from, when it came from, they've signed off on it, has it been changed.
And it sounded like you're starting to get into like selective sharing. The permissioning, it's not just fired off to the world and lose control. I can, as the data and asset owner today, I can choose who to share that data with.
Pat O'Meara: Not only can you choose, but you can begin to create pipes to different compute functions. So right now think about, I wanna prove the state of my asset so I credential all the data and we'll talk about how we do that. And then you say, well, I want somebody to value this.
Right now to get a mark on your asset, 80 to 90% is data collection and data entry. We can make it so you can literally pipe that data directly into a valuation tool, but also a waterfall tool, an investor calculation, distribution, expense allocation. So anything where there's compute, you can push that data directly into the cell. And that cell has the in period data, but also a pointer to what the calculation is.
So anybody who's ever been in private equity or finance, you've gotten an Excel spreadsheet from somebody and you're trying to decide why I14 was divided by I32. You spend a week on it. You can't figure it out. You rip it down, you read the docs yourself, you rebuild it. But if you have a large fund, you can't do that. But turnover, there is huge.
What we're doing is we're credentialing here's the in period data element. But then the calculation is algebraically defined, every variable points directly to the limited partnership agreement, the side letters, all of those things. So it's a hundred percent auditability.
As we do this. Here's the source document. Here's the hash I can prove who created it when, and I can prove it hasn't been altered since it was created. Now here's the seven different calculation tools that rely on data elements from here. And so we extract that data, push it into a calculation tool. That calculation tool comes up with a number. That number then impacts a collateral calculation. It impacts all sorts of different calculations.
And then if this top level document changes, we can immediately show here's all the dependencies that were created through a series of hashes, pointers, and links. And we can update each one real time so there's a renewed auto calculation, et cetera. So if I'm in an investment committee, I can say, is this information real time, I hit one button and it can make sure that every piece of information that I'm relying on is real.
That also allows us to do things like cross border and cross jurisdictional trading without needing some world's large white list. Right. But now I can do spot audit, compilation at moment of trade. And I can prove that audit with a series of hashes.
Jared Klee: You're talking as a practitioner, not just as someone building a solution for this market. So Pat, if you don't mind, like prior to founding Inveniam, what were you doing? Who was Pat before Inveniam?
Pat O'Meara: Hopefully who Pat is, is the same, but what I was doing was slightly different. Right. I worked at Raymond James. I worked at Bear. I left, I started my own investment firm, ran that for 14 years. In a little niche, we were the globally dominant player. I sold that company. CIO of a university, just over a year there.
And then I started managing private equity for a Forbes 400 family, one of the generations, and I was working together with them. One of our core theses was that because of overregulation banking functions were gonna be decentralized. And so we said, okay, how will these new markets where non-bank lenders are gonna start lending a ton of money, where are the markets gonna form? It's not gonna be regulatory driven. We think it's gonna be technologically driven.
And so we said, what are the technologies? What's called physical settlement, where you sign a piece of paper and at closing, you go around the conference table and you sign nine different sets of docs, and everybody takes their copies, but instead they get physically settled. As these markets go from physical settlement to digital settlement, that's where the market's gonna be.
And we started looking at those technologies and in 2015, I was introduced to the distributed ledger and I thought, oh, this is unbelievable. It's gonna change everything.
My old firm, we were municipal securities advisor and probably 80% of the debt that we helped advise on was tax exempt. When you would close a deal you would get a big book, green or blue leather bound book, it would sit on your bookshelf. And one, it told people how many deals you'd done.
But the other one is when that deal blew up, because deals blow up. Invariably, it doesn't matter what happens. You know, the real world occurs. You go there cuz that's where all the docs are because you're gonna rework that. Right. You're gonna re rework the loan within the confines of the legal structure.
I still remember in '03 or '04, I got my first leather bound book. And in the back, there was a, a sleeve that a CD was in. And I was like, this is amazing. data all the Within two years, everybody gotten rid of all of those books, cuz all the information was there.
This is the same thing, except in addition to all the original documentation, we can instrument it so what it says we need to measure, we can measure real time into the underlying performing asset to make sure we're living up to our legal covenants whether it's at a fund level, et cetera. And as we can start to feed these things that have real surveillance where oracles like Cushman and Wakefield, JLL, CBRE, Houlihan Lokey, Mercer, Deloitte, ValuStrat, Baker Tilly, they start valuing assets with observable inputs, sophisticated model and in period comps on a quarterly basis.
We now change these illiquid assets, real estate, infrastructure, private equity from level three, illiquid assets to level two marketable alternative. That changes accounting treatment, that changes capital requirements, provides regulatory capital release. And that's the foundation upon which digitization will occur. And from there, secondary trading will come next, new novel forms of primary issuance.
But nobody's gonna issue paper and nobody's gonna issue funds and nobody's gonna do any of those things on a secondary basis until they're certain of all the accounting treatment, regulatory treatment, et cetera. We don't need secondary trading for us to add huge value to clients cuz we're changing how it's being accounted for because of better data. And it allows them to mark that asset on their balance sheet.
So if I own a piece of real estate that I bought, I buy it at one price and then I'd depreciate it over time. That's called book minus accumulated appreciation. Using better data moving from three to two, you execute a capital markets transaction alongside our software, you can now carry that real estate at fair market value. That's huge value. Think about hospital systems, universities, major corporations, funds, pension funds that hold assets of book minus accumulated depreciation.
So real estate. It's one of the reasons people invest via funds instead of owning the asset directly because they can't carry it at fair market value. And even though they like the cash flow, the depressed market value, if they've held that asset for 15, 20 years, that building might be worth 25% of what it's really worth on their books. And if we can unlock that value, it's a more accurate representation.
And this is what happened with high yield bonds. High yield bonds went from level three to level two. And even though everyone is different from a security and an asset perspective, the market grew 10x, trading grew 100x.
Jared Klee: I want to come back to like what the world is today. If I'm a church or a hospital or take your pick, if I'm a fund, manager first off, what is a level three asset to me. Secondly, like if I'm going out and either acquiring one of these or I'm selling one of these, at the most detailed level mechanically, like what is the process today?
And I'm particularly interested in like how many gazillions of parties am I engaging with to get to the point where I feel comfortable or the buyer feels comfortable? How long is that taking? If we're talking lots of paper, data across lots of parties, usually that means an extraordinarily painfully long time to get deals done.
So I'm really interested cuz Pat again, you've lived this and you're solving it. Does that deal flow, deal structure look like today, the process to get a deal done?
Pat O'Meara: We're dealing with one of the top 10 sovereign wealth funds in the world as a user of our software. We just processed a portfolio that they valued at the fastest, they would value that portfolio and it would take two and a half months for them to value. They would typically only value it once a year, but sometimes they would value it four times a year. And their output in that valuation was a PDF, right? So here's a PDF, a hundreds or thousands of page PDF.
Jared Klee: But before we get to Inveniam, who are they engaging to get that thousand page PDF? are the inputs that are taking two and a half months to go stitch together?
Pat O'Meara: I am big sovereign wealth fund, I'm CalPERS, I'm GIC. And my real estate sleeve is $120 billion, that's my equity, which means I own on $120 billion, $300 billion of real estate. That's a big portfolio. The entity we're talking about, they would use all their pricing power to get all the big JLL, CBREs, Houlihan Lokeys, ValueStrats to bid. And they'd say, I will give you one mark a year for $16,000 per building and that's really reduced pricing, right? That's using the greatest leverage, right? If I own a small one, I might be paying $30,000 to as much as a $100,000 an asset.
And then what they're doing is they're collecting everything from the Yardy data, meaning about leases, lease abstractions, foot traffic, maintenance of a mechanical system, motion activated light sensor, energy usage, toilet flushes, water, is the building green or not. The primary mechanism is water usage and electric usage per square foot.
But like in New York City, older buildings, the meter is not a building owned asset. It's a tenant owned asset. And so if somebody buys a building thinking that it's a green asset, that it's a Leeds Platinum, but one third of the energy meters for that building were held. And in the acquisition, my platinum just became silver. Because all of a sudden, if I have real math and they just go, ah, I'm not sure I wanna own this anymore.
You're looking at a building built in 2016. Even if I was built in 2016, I have to do a hazardous materials report saying did anybody import asbestos into a building that was built 30 years after everybody knew asbestos was bad, but I still have to do the report for that purchase for $30,000.
Jared Klee: All of this stuff. This is coming over, what PDFs and Excel docs in email? That there's now an army of people they're sitting there just like copying and pasting and building their own.
Like, that's a nightmare.
Pat O'Meara: Right. When the entity is public, like a publicly traded, so you have a big, publicly traded real estate concern and they have to get a mark that's public quality because they can't prove it hasn't been altered since the last time they saw it. Every quarter, they have to get a certificate of good standing from the state of Delaware.
For every so every quarter I need to get a new certificate of good standing from the state of Delaware.
Now, future state, they can see it. They can sync it, they can show, they can cryptographically prove it hasn't been altered, and they can show that it's still in good standing. Suddenly, literally an automated function compares the hashes. Boom, here it is. We can prove that this is the real one, it hasn't been altered, and we can cryptographically prove this is still a valid certificate of good standing. And you only need to pull it once a year instead of four times a year.
And so you're collecting all of these data elements. For this portfolio that we just did. They opened up their SFTP. Now we had uploaded our software before and gotten everything ready. So they said, okay, we're gonna do this. You're presenting to our board of a sovereign wealth fund in four business days.
So you've said you can do this - let's go, brother.
They opened it and they gave us 1500 documents. Right. And they downloaded it via SFTP. We anchored all those to blockchain. We used our extraction tool, which read them, sorted them. We extracted 3000 documents, delivered it to the valuation agent. All of the information was directly into the what's called their Argos upload file.
They looked at it, they prepared the right comps for the portfolio. They delivered it. On the fourth business day, when we sat down and we took this sovereign wealth fund through the demo. The guy who had turned on the key to our data kept saying, "this is amazing, this is amazing."
Cuz all of the data was anchored, but not only that, their input was not a PDF, they got a evaluation, but the valuation agent had actually used all of the data, put it into our tool and the output was a JSON file, which we can port directly into what's called iLEVEL Addepar Efront, which is the portfolio tool that these guys use.
So instead of a physical document, they got a digital document, feeding, and everything they could click through. And there was a hundred percent auditability where we could see here's where the document was created, here's the chain that it's anchored to. In the anchor, in the chain is the hash, so that in three years, when somebody wants to go back, we rerun the hash, we run the algorithm, get a new hash compare what's in there. And we got a timestamped mechanism to prove, is this the real document that we're still relying on.
This ability to prove compliance. Prove state of an asset way into the future is enormous. And so we were able to deliver in four days a mark on an asset. You know, we had done about eight days of prep work, getting them on our software, et cetera. So two weeks or less, what was a two and a half month process with an army of people.
So we can literally deliver a mark for a thousand dollars a mark. And instead of having to give all your business to one person, you can give it to anybody you want. I want JLL, CBRE, whatever, to do a mark this quarter. And I might want two or three of 'em on this asset, cuz I think it's value's in question, I want different models.
And not only that, the data's real time and I can put if then functionality into it where I can automatically check what's their cash balance, what's their foot traffic, what's their lease payments. And what this even does is one step deeper.
Because with that granularity of data, you can start to create new mechanisms. So just like Stripe and Plaid, that on the consumer lending, they get in between the electric bill and the rent bill. Jared, you get paid on Friday and that they get their payment right before you go to the bar, right. Until they're gonna say, Hey, listen, don't let, 'em go to the bar after payday. Right. Cause there'll be no money left.
So we literally can do this on the lease payment through an app, but instead of money going into a lockbox, when it goes into default or REO, we could literally strip pieces of that payment, every atomic rent payment or lease payment that a certain percent goes to the senior, certain percent goes to the mezz, certain percent then goes to the, the operating that they use. A lockbox is a horrible crude instrument for a building that's in distress, cuz then the bank has to operate it.
But if they could just say, I want 25% of every lease payment, the second it's paid off the app by the tenant, it automatically gets routed to me. The cost of money's gonna go way down. We're just creating abilities to slice and dice data.
And because there's no intermediary, the opportunity for fraud goes down. The opportunity to have somebody mess with documents post fact, post trade goes to zero, right? And what we're doing is we're just creating a mechanism, a more automated visibility into the systems of record real time.
Jared Klee: You're unlocking trapped capital. You're creating a faster flow of money. We're talking about programmatic money, at this point. You can direct it where it needs to go as it comes in to where it needs to land. I'm sure we're gonna come back to tokenization as, as a mechanism against this in a sec.
But something that really caught me Pat is just this scale of the ecosystem that we're talking about here. In eventuality, a huge number of folks get hooked into this thing. Today, and I've seen big headlines, Apex and Kushman Wakefield, and so on. Today who is hooked into this as a data provider? Who is hooked into this, perhaps the right term is as a user, as a customer, who's consuming that perhaps to get a mark?
Pat O'Meara: So we feed different computational systems, Advent Geneva, Cascade, ValueD which is Deloitte's valuation tool, Investran there there's just so many industry standard accounting, valuation, computational tools, and we feed that data real time into those, all these different tools, Excel, the dominant tool, right.
We can feed those real time where you can see not only the in period data element, but also what the calculation is itself. And because we do that, it allows people to step into digital. And what that does is each calculation that's done in those various different tools. With a flick of a switch, we can not start feeding through an oracle. A smart contract.
So I don't care whether you wanna do the calculation in a smart contract or an Argos or ValueD or Excel or Cascade. We can do that. But we're creating the mechanisms where the data flowing is there, but not only that for a big bank, their SOC2 covers all the way through the process, including wrapping the node that's speaking to the smart contract.
Jared Klee: You're talking trusted pipes and plumbing from the source through to we'll call it the source of record today, source of record, source of the long list of tools you gave. Because we know we've got this trusted pipe of data coming in, if you wanna consume it as a traditional asset on a piece of paper with the nine copies around a table, have at it. If you wanna consume it as a digital asset, that as a token, that gives you the full audit trail, going all the way back, unlocks access to that full pipe. You can have that too. And it's not hard to guess where people eventually are going to end up.
Pat O'Meara: Correct. And so iLEVEL, Addepar, eFront, the three biggest asset portfolio management tools can sync all the way back through an interval fund, a closed end fund or a single asset. At the top level, the portfolio, the fund, down to the asset. We can click all the way through. From there through the custodian, through the administrator, through the computational tool, all the way through the node and the or the Oracle that speaks to whatever that is to the underlying data system. Whether it's an Amazon S3 bucket, whether it's in Box, Dropbox, it's your own custom, it's a Citrix server, whatever it's in, we can see not only the source document, where it's token based access control, but also we can prove on chain.
None of the data's on chain, just the mechanism to prove the provenance of it. Cause every the data is moved, altered, or improved, we anchor that to the chain. So you can see the provenance, the chain of custody, of the data, and the fact that we can deliver that from your Addepar or your eFront, that changes, how banks think about these things. And we spent a lot of time getting the ability to deliver a JSON file and we could push into these portfolio tools. But the funny thing is all of our early adopters, what we're mostly feeding is still Excel spreadsheets.
Jared Klee: So you've dramatically lowered the barrier for someone to hook up to this system, cuz it's like, look, if you wanna upload PDFs to Dropbox, we'll deal with it. If you want to upload it, I don't care where it goes. We'll consume it however you throw it at us. We'd prefer in the future that you kind of get your act together, grow up and deliver digitally, but we're not gonna force you on that journey.
However you bring it, we'll consume it. We're from that starting point of what you've delivered, we will create the authenticated, provable audit trail of what that data is all the way to the eventual system, Excel, eFront, you name it, that acts legally as the source of record. Great. If that's the end point for you sounds good.
But if you wanna take it a step further, we will unlock tokenization and the like where you can have a digital representation of that asset that we can trade around and so on that has that entire trusted pipeline too.
Pat O'Meara: We wanna have a digital conversation. And in that digital conversation, we need to know that if you buy this thing, you have rights to this thing, right. This building, this company, this whatever. Between the chancery court state of Delaware and Satoshi figure those two things out. But if we're talking about an asset and we want to get it to bid or ask, and I don't care whether you're talking about a lollipop, a vaccine, a building, or a company.
You're gonna say I'm willing to buy this lollipop if it hasn't been licked before, right. I'm willing to buy this vaccine if I know it's been in cold storage the whole time. I'm willing to buy this building. If you've maintained the mechanical systems correctly, and this is the lease.
Now, normally what would happen is with the building. What you're doing is you're literally sending somebody in to comb the records and opine on them. What we're doing now is, on a short interval basis, you can anchor that data to the blockchain so you can do real time audit of that. And you can diligence the asset in days or hours.
And the same thing with the vaccine. I can prove that through IOT devices, that this is the temperature it was stored from, and this is who created it. I can talk about a lollipop. Little harder, no IOT devices, but you know what I mean? We'll take attestations, but you know, whatever it is that if the thing...
Jared Klee: Look Pat, I'm not sure I want an attestation on a lollipop....
Pat O'Meara: Yeah, there you go.
Jared Klee: It's lemon flavor. I'll attest to it. Like, yeah, I'm not interesting anymore.
Pat O'Meara: Alright, there you go.
But, but the bid ask, as you know, this is called the excluded middle. We wanna be able to have an argument that there's only two possible outcomes bid, ask. If there's contingencies, the bid goes way down or you leave the market completely.
If we can credential all of those contingencies, we can have that bid ask. And our ability to credential the state of that asset real time, value it every month, allows people to have bid ask discussions where they know that the performance of that asset is being looked at once a quarter, once a month, once a week by a third party oracle.
And what that's gonna do is it's gonna unlock value. So banks are gonna lend against assets. People are gonna be able to trade in and outta capital stack. People are gonna monetize in new ways. And we're gonna think about store of value, cuz if you can get out, you'll get.
Jared Klee: Before we get off the deep dive on private markets. I absolutely love this. I want to come back to that level two, level three asset statement you made before. It's a fairly nuanced statement, but has massive implications.
So Pat, if you don't mind, like what is a level three asset? What is a level two asset? Where is that terminology coming from?
Pat O'Meara: So this is ASC 820, the accounting regs ASC 820, FASB, 157, IFRS 13, where you're laying out level three is an illiquid asset, level two is a marketable alternative, level one is liquid asset, which means in period, I can see the exact same asset traded.
Level two is a marketable alternative. That means there's other like assets that are trading, but not this exact thing is traded. Level three is this is an illiquid asset, one of the three things are missing. There's no in period comp, there's no sophisticated model that's trusted, or I can't observe the inputs.
Inveniam is solving for the observable inputs. Kushman, JLL, CBRE, Houlihan Lokey solve for the model and they also for the end period. So the thing that has kept real estate from trading like high yield bonds, which are the loans against the actual underlying asset itself, has been the ability to source the input elements. So, because we do this, this changes how you hold it on your balance sheet, the capital reserves you need against it.
So a bank, if you own real estate and you hold it as a level three, it doesn't matter how valuable that real estate is. You can't count it towards what's called your tier two capital. If I start getting quarterly marks and all the inputs are there and I carry it at level two, my auditor validates that, which Deloitte as one of our partners will validate that, you know, if you're using our tool, and then literally you can change your tier two capital as a bank, which changes what you dividend, how solvent you're viewed.
But this is the same thing for a pension. When you have these things OPEBS, these pension employee benefits, that you have, how much do you owe your pension? How much are you underfunded? People who own a real estate asset, a core real estate asset. Low cap rate and they're paying a third party to manage that asset. And you'd say, why don't you just own that yourself, because I needed somebody putting a mark so I could at fair market value.
Now I can hold this on my own. Let me give you an example. An insurance company holding a real estate asset has that real estate asset on what's called Schedule BA 20% capital reserve. To get Schedule A, I used to have to pay a fund manager to manage it for me. That goes from 20% to 10. They would pay one and 10, two and 20 for somebody to manage that.
Now they pay us four basis points and they can go from 20 to 10. And all of a sudden I can hold that real estate on my balance sheet at 50% of the capital reserves because the regulator can see real time data and an in period mark.
We're working with a Fortune 30 company right now, it has an enormous amount of real estate call it 13 and a half billion that we're looking at. They're carrying that at 2 million dollars. They have taken that all the way. They've fully depreciated it to $2 million and using our tool with Kushman and Wakefield and Deloitte, we're working with our audit subcommittee, where they're gonna be able to carry that at fair market value. That's and a half billion dollar bump in their equity.
We're working with a healthcare system in the Mid-Atlantic. They have just under 5 million square feet of real estate. They were carrying it at book minus cumulative depreciation because of these marks. Kushman giving them a quarterly mark on these assets, we're adding $700 million of value to their balance sheet. They're getting a total return swap of $200 million against the buried equity that was in there.
So they get 40 days of cash on hand, $200 million, $700 million bump to their balance. Their cash goes up. Their debt to asset goes down and the bank that's lending against the buried assets, cuz they have the better data and they have the in period marks, they're lending. Inveniam's mark to the bank is the thing that allows them to do this transaction that they never could have done before.
And for them it's a no brainer. My cash goes. My assets on balance sheet go up, my debt to equity or debt to assets goes down, and they're just going, this is a no brainer. Everybody who has assets that they fully depreciated or partially depreciated that has real value that they're using today, they're gonna be able to pop their balance sheet and improve their credit rating.
Think about your university. It's a couple of years old, right? It's been around the block a few times. It's got dorms that people are using. And even though they've improved them, the value of that building, that dorm, has no relationship to the cash flow generated by it. And we can allow them to provide greater granularity to those underlying assets, which changes their accounting. It changes their borrowing costs, changes their balance sheet, how the market sees 'em, et cetera, because it's better data.
Now, by the way, there are some people who hide bad assets in their portfolios. They don't like us.
Jared Klee: I wish them the best of luck.
Pat O'Meara: Yes, yes.
Jared Klee: Pat, there is a long, long list of topics I think we're gonna have to leave for another conversation. There's so much more to unpack with Inveniam, the work you're doing on tokenization, the work on the public network. We're gonna have to have a follow up on those.
I want to look to the future here, cuz what you've described is enormously powerful. We've focused on largely on real estate because I know that's where Inveniam is doing an enormous amount of work today. It's expanded into private equity. I'm sure there's others that I don't even know about.
I'm curious, like, I don't know, five years, 10 years, 20 years, whatever an appropriate future look is, what is Inveniam at that point? Both from a company standpoint, as well as from a user standpoint.
Pat O'Meara: We wanna be an operating system for data where we're commuting trust in the data, of the source of that data. And if you have any automated computation or automated calculation that the source documentation and where you derived that data from, if it's not validated by Inveniam, you're not gonna trust it. There has to be a mechanism to credential data.
This is one of the things about Inveniam, we're a tool. We're a utility where nobody's data is ever in our system. We give you the tools to credential your data and then monetize it. But it's literally never in my system. I'm not in there. I'm giving you tools or I'm giving Kushman or JLL or CBRE tools for them to credential data better, quicker, faster, and deliver it into other systems where they can see the source documentation.
But Inveniam is an operating system for data, similar to where you have an operating system for your phone, that all the apps work on. Everybody's building all sorts of stuff, but you build it where you say my mechanism of adjusting data is Inveniam.
Jared Klee: That is the definition of pipes and plumbing and it unlocks so much value. The tracked capital, the ability to have real time updates. The ability to narrow that bid ask spread. I mean, we're talking the fundamentals of how finance works, price discovery, liquidity.
I mean, we can go down the list of buzzwords here. But underneath it all, all of it rests on: do I understand what it is I'm buying and do I understand it the same way the person across the table does? And if I have trusted data, we can establish that. And a heck of a lot of stuff becomes a lot easier.
Pat O'Meara: We're a notary. We're a real time short interval audit of a digital form of notarization. That we're not saying what you're saying is true. We're just saying, you said this and it hasn't been altered since you said it and we can prove that.
If it's untrue, there's a consequence. And if it is true, there's another consequence. But we're providing the completeness of the data set through transaction through transfer, through data, lost and recovery. We're showing completeness of dataset. That is massive.
Jared Klee: Pat, it's just awesome. It's just awesome. And this has been so much fun.
Pat, I ask everybody the same final question. What's the biggest win that you've had? Could be personal, could be work, wherever you want to take it.
Pat O'Meara: The biggest win for anybody who's ever met me knows it's my wife. Is the biggest win. And by the way, I keep trying to win it, cuz it's not a one time activity. And so I wanna say my wife, my family are my biggest win.
The other big win that I'm gonna add on to that is in personal life. Early on, I had some mentors who helped me understand and prioritize the need to inculcate taking time to pray, taking time to read, taking time to be curious, and being a full person, and not be two dimensional to the market. None of the things I'm doing today, if I had remained one dimensional would be possible early in my career.
So the biggest win is my family. The second part is being a full human and not trying to be a one or two dimensional person, but a full one.
Jared Klee: I absolutely love it. Thank you so much for coming on today. This was so much fun.
Pat O'Meara: You're the man. God bless you, brother. Thanks for having me.