Epicenter - Learn about Crypto, Blockchain, Ethereum, Bitcoin and Distributed Technologies - Pareto: Customizable On-Chain Private Credit Marketplace - Matteo Pandolfi

Episode Date: August 25, 2025

Built primarily for institutional-grade clients,  Pareto delivers customizable on-chain credit markets designed to expand DeFi liquidity and TradFi tokenization through structured yield strategies tailored to diverse risk profiles. Pareto allows its users to construct individualized credit lines in specific risk-ajusted tranches, with custom: interest rates, lockup periods, withdrawal cycles, reserve ratios, etc. In addition, Pareto’s USP is an yield-bearing synthetic stablecoin, fully backed by major stablecoins, that can be deployed into a diversified portfolio of liquid, short- and long-term credit, thus increasing capital efficiency.Topics covered in this episode:Matteo’s backgroundIdle Finance yield optimizationPivoting to ParetoInstitutional borrowers in early DeFiCompetitive advantage of ParetoOutsourcing underwritingManaging defaultsCustomized lendingKYC requirementsTimeline terms ‘marketplace’USP, Pareto’s synthetic yield-bearing dollarLegal framework & credit allocatorsUSP yield, liquidity & integrations‘Opaque’ credit vs. DeFiPareto smart contracts and redeemsSuccess in on-chain credit marketsEpisode links:Matteo Pandolfi on XParetoPareto on XIdle Finance on XSponsors:Gnosis: Gnosis builds decentralized infrastructure for the Ethereum ecosystem, since 2015. This year marks the launch of Gnosis Pay— the world's first Decentralized Payment Network. Get started today at - gnosis.ioChorus One: one of the largest node operators worldwide, trusted by 175,000+ accounts across more than 60 networks, Chorus One combines institutional-grade security with the highest yields at - chorus.oneThis episode is hosted by Friederike Ernst.

arbitrage opportunities are not always available. And so the funds that we were using to deploy into the arbitrage bots were idle for some time. So we were like, okay, we need to find a way to make that more efficient. In 2022, we realized that most of the customer base for idle finance was to do you show funds allocating across different strategies. And one of the major feedback that we received at that time was that your doctor optimization is great, but we need to take care. But we need to take care of risk and risk diversification.

So at that time, we decided to introduce yield the trenches. Credit lines can be really customized from underwriting terms, covenants to compliance requirements. This is something that, like, for example, maple or centrifuge is a bit limited, I would say. The credit lines that we have are curation-based. So we are not the only one that are underwriting this kind of credit lines. but we opened up these processes to third-party curators. Welcome to Epicenter, the show which talks about the technologies, projects and people driving decentralization and the blockchain revolution.

I'm Friedricha Ernst, and today I'm speaking with Matteo Pandolfi, who is the co-founder of Pareto, a credit coordination protocol that evolved out of Idleau and is building on-chain markets for private credit. Before I talk with Matteo, let me tell you about our sponsors this week. If you're looking to stake your crypto with confidence, look no further than Corse 1. More than 150,000 delegates, including institutions like BitGo, Pintera Capital and Ledger, trust Corus 1 with their assets.

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All you need is one GNO and some basic hardware. To learn more and start building on the open internet, head to NOSIS. I.O. NOSUS, building the open internet one block in a time. Mateo, it's super nice to have you on. Really excited to be here. And yeah, thanks to the entire Epicenter team for hosting this session to all of you for tuning in you as well. Cool. Mateo, tell us a little bit about yourself before we dive into Pareto.

What's your professional and academic background? Yeah. So before founding Pareto and as we're, going to go through and more into details, Idle Dow back in the past. So my background is in finance. So my academic career was pretty much in finance and entrepreneurship. So it's kind of like a good mix between that that brought me into defy this kind of like, you know, innovative market, but still really related to finance. Before actually starting with Pareto and I do that I was working on financial risk analysis.

So I was consulting with major financial institution in Italy, like Intisa San Paolo, for example, on their credit desk. So essentially, doing helping on the writing process and due diligence process in order to create these kind of like corporate bonds instrument for these financial institutions. What drew you into the blockchain space in the first place? Oh, that's a really good question. because I've been brought into the DFI space by my other co-founder, our CTO. And who made me find out about Ethereum at first?

At that time, I was actually still a finance student. And we were exploring Ethereum. He had a background in computer science. And with my background in finance, we were thinking how we could build something. on Ethereum. And the first instance of something that would build on chain was actually touching the arbitrage and arbitrage bots. So, you know, what we know right now as MED,

at that time was still called PGA price gas auction. So we started building these kind of bots that were looking on at discrepancies. between checks and dexes and arbitraging price across these assets. And yeah, so that was kind of like the first instance and the first way where I realized that we could really create something that was completely programmable and automatic and was really like changing the way that I was used to see finance.

Because, you know, from the academic, but even from the professional back, I'm always saying finance being quite sealed. So all these kind of closed system that we're all like communicating internally and not to each other. And with Ethereum that was like the first time that it was my ha ha moment. It's like, okay, that that's really composable and that's something that we can build automation that runs on chain and runs 24-7. So that was the first time I really touched with my hands, Ethereum and the power of smart contracts.

And then, you know, I just got into the rabbit all of that. So we started exploring lending protocols. That time there wasn't even a other. It was only compound and the YDX. And so then everything evolved into what brought us into idle finance and then also parato later on. When did you decide to kind of discontinue the arbitrage bot? That's a good point because idle finance came out from a need that we had for the arbitrage bots

because actually, you know, arbitrage opportunities are now like always available. And so the funds that we were using to deploy into the arbitrage bots were idle. for some time. So we were like, okay, we need to find a way to make that more efficient. And so I would say that we proposed idle finance as a way to optimize the yield on idle funds in 2019 on an accatoner on Gitcoin. So I think that was in 2019 when we decided to focus completely on an idle finance and put aside the arbitrage bots. So I would say 2019. We started the arbitrage bots back in 2017, 2018.

So, yeah, we ran that for a couple of years and then decided to focus completely on idle finance. And was the rationale for kind of moving over purely a return on investment kind of play? Or what were the drivers here? Scalability. One of the major drivers were scalability, because with the arbitrage bots, we saw that by increasing the AUM, the TVL of the arbitrage bots, we were actually reducing the margin of the funds for the arbitrage opportunities.

So we were really focused on building something on Ethereum that could be scalable, you know. So when we started implementing the very first version of idle financing into our arbitrage bots, we realized that we could manage $1 million to $100 million. and the result was pretty much the same in terms of return of the capital because the kind of optimization could be applied with more capital compared to arbitrage bots. So building something that was able to be scalable and to be offered also to a more broader audience, I would say,

because arbitrage in general is quite a niche product or in general it's a niche concept that not a lot of users grasp or understand in general. Instead, like, automating the yield generation optimization, optimizing yield generation across different protocols was really something that was clicking

with DFI users at the time. So I would say, yeah, scalability and also being able to offer this kind of product to abroad their audience and let them understand the product to a broader audience was the main driver of us focusing completely on idle finance. There were quite a few projects that kind of centered around that, right? I mean, in the very beginning, it was things like insidap that kind of let you kind of switch funds between Maker and Aver memories of Scragly. and then kind of more sophisticated things like Jern came along.

So how did Idle Dow kind of fit into that landscape? So I think we had the lucky and the opportunity. We have been lucky and we had the opportunity also to meet like Instadap team or even Andre Kronja from Byrne, even before them building out their products. I would say Instadap is being really great, that they have been really great builders, but never really focused on yield optimization and automation of that yield optimization.

They were more focused on providing great tools for borrowers that were using, like, for example, compound, AVE, or even microdial. And I would say that Instadap falls more into the, into a different category compared to idle finance. Why Earn and Idol finance are pretty much similar. Actually, I remember a lot of conversation in Telegram with Fandre at the beginning on how to solve some, like initial issues of yield optimization.

Like there was this ping pong effect that we found out at the time that was affecting yield aggregators, which means that essentially when you move, a big chunk of the funds into a specific lending protocols, you also influence the interest rate on that specific protocol. So if you don't have control on the funds and control on the influence that you have on the interest rate, you might end up into a ping pong effect,

which means that you move all the funds from protocol A to protocol B because protocol B has the higher interest rate. But when you do that, you're lowering the interest rate of protocol B. and might become lower than the protocol A. So the yield aggregator sees that the higher interest rate is again on protocol A. And so you move back the funds from protocol A. So you see that you create this kind of ping-pong effect between by moving a rebalancing fund. So we have been like talking a lot and understanding what was the right, you know, algorithm and optimization mechanism to tackle.

also with fund retrocourns at the beginning. And then I think why earned it a great job on, I would say, the positioning and narrative built around the yield aggregation. At the time, we were quite, you know, for starting idle finance, as I mentioned, we started with a Gitcoin Aketon.

So we won that GITCoin Aketon, and then we got accepted into an accelerator in New York. York with consensus. And so we kind of took a more professional approach, I would say, or institutional approach to the product. Instead, I think at the very early phase of WIREN, they took more adhesion approach, which turned out to be the right narrative. So I would like say that they did a great job on that side of things. And of course, then the dev team and the community that formed around WIREN was really great.

So congrats, of course, on WIREN and Andre Cronge on bootstrapping these at the beginning. And I would say that we kind of, at the end of the day, DFI was a small market at the beginning. So the way that we were looking at competitors, at the beginning, was more like competition, rather than pure competition. And so it turned out that like one of the major

partners for idle finance was WIREN itself. Like some of the strategies and the votes that WIRE had at the beginning, like for USC, USD, and I were based on idle finance, the optimization for a big chunk of the funds that they were managing. So it turned out to be kind of like more a partnership rather than a competition with wire and finance, for example. Of course, over time, DFI market evolved, become more sectoralized, more professionalized. And of course, competition came out.

But I would say that early times of DFI, I really enjoyed the early times in DFI because it was all about, like, cooperating together and trying to build like, you know, all the legal pieces that you could put together in DFI. It was really about this sentiment, was really about these. this philosophical, you know, work together to grow the market instead of competing together to shrink the market to each other. What ultimately kind of drove with a pivot from from Idle to Pretto? I would say that we focused a lot in for on EOL optimization from since 2019 to I would say, 2020. In 2022, we realized that most of the customer base for idle finance was institutional funds. So institutional funds are locating across different strategies. And one of the major feedback

that we received at that time was that yield optimization is great, but we need to take care of risk and risk diversification. We need to mitigate risk for the liquidity providers. So at that time, we decided to introduce an additional product line and an additional primitive to the product suite, which was yielded trenches. So essentially a primitive that could, where we could build the senior and junior trenches, senior mezzanine junior trenches on top of potentially any defile source. And so this was a response to this kind of feedback that we received. And the cool thing is...

And senior and junior trenches in this context kind of being different rates of return for different levels of risk, right? Or do you mean something else by that? No, no, that's correct. That's correct. Essentially, senior trench is the most protected vehicle investment world that is protected by the junior trench. So whatever there is a default because of a knock or a loss of funds by the borrowers or these kind of loss of funds, Uniors are first loss absorption layer. So they absorb the loss on the alpha of the senior.

Because of this risk that they bear, they receive also higher yield compared to the senior trenches. So we introduced this primitive. We started building around different kind of yield sources and defy over collateralized landings, staking in order to understand also where was the product market fit for this kind of product line. And we realized that most of the product market fit

was on institutional credit. At that time, we were working with protocols like, you know, Maple or Clearpool that were doing these kind of first instances of institutional credit on chain. And we saw that like liquidity providers and lenders were really appreciating senior and unit trenches for institutional credit lines. Because different credit funds,

different hedge funds or families offices had different views on these specific institutional borrowers they were lending to. And so using senior unit trenches allowed them to customize the risk reward profile of their entire credit exposure of their entire credit portfolio. So we realized that most of the product market fit was there, but we received also a lot of feedback from both borrowers and lenders that the credit infrastructure was not ready for institutional needs. It was really kind of like mimicking compound and have an interest rate model, which was a paying for the borrower because it was a single dollarware that wanted to, with a variable interest rate that operationally speaking was terrible because they were looking

more at the interest rate that they were paying compared to doing their own business. And in general, the terms and the underwriting process for this kind of institutional credit lines on chain at that time wasn't really customizable and modular, I would say. And so we realized most of the product market field was there. There was room for improvements on the credit space. So we said, okay, we need to, we have. have a clear opportunity over there and we wanted to build and improve that space, that part of that defy sector, let's say. So that's pretty much how we transitioned to Pareto. We started working a

lot with institutional credit lines and then we realized that we wanted to improve the credit lines themselves. And that's how essentially Pareto came out. Tell me more about the institutional borrowers. So So kind of what kind of institutions were they that they were willing to kind of borrow in this very competitive market on chain, where kind of you can go to your local bank and probably get a more competitive loan? That's a good point because, of course, they could access, you know, could originate on credit lines from a traditional bank. but the process of origination takes a lot of time, especially the kind of borrowers that we're working with right now are pretty much institutional funds that run delta-neutral strategies or market makers or prime brokerages.

And the process of originating a loan and managing that loan in a traditional way usually takes a lot of time and resources from their team. Usually the teams are not really huge. And so the overhead is really tangible for the final borrower. We recently actually run a use case with one of our major borrowers, which is Falcon X, one of the leading market prime brokerages. And what came out of the use case is that before using on-chain credit lines, so relying on traditional credit lines,

took around 80 hours per month from their team to make sure that in order to originate all the documentation was there, making sure that all the lenders were aware of updated terms and also doing manual reconciliation. What came out is that now with the on-sharing credit line, they have to dedicate two hours per month, the same team. So operationally speaking, the improvement for the the borrower is really tangible. There's a streamlining process that is happening on the operational side of things.

You know, on-chain credit lines are pretty much self-operating compared to a traditional credit lines. So that's, I would say, the main advantage of operating an unshane credit line. And secondarily, I would say also. being able to have a credit position that is composable is a big advantage for these kind of borrowers. And a big advantage, I would say, also for the lenders at the end of the day. Because, you know, being able to use a credit position as a collateral in Avamorfo oiler, for example, or create an interest rate swap instrument using Pando for the same credit position,

it's really powerful for the lenders. So lenders have a better, let's say, U.X when lending to this kind of institution. And in terms, borrowers are able to originate more liquidity with these kind of credit lines and streamlining the process of managing these kind of credit lines. Cool. There's a couple of projects kind of doing very similar things in the space,

so kind of the likes of maple and centrifuge and so on. So how is your approach different or is it different from your competitors? So it is different. I think center foods, they started like really early. So they did a great job at, you know, pioneering on this kind of area. And also Maple, they kind of pivoted. I remember back in maybe it was 2020, 2021. And then they focused completely on. on-chain credit. So both are doing great jobs on expanding this kind of space. The main difference that we wanted to implement since the beginning of operator

was to make sure that we have a highly customizable protocol. So credit lines can be really customized from under writing terms, covenants to compliance requirements. And this is something that, like, for example, in Maple or centrifuge is a bit limited, I would say. But also, and more importantly, the credit lines that we have are curation-based. So we are not the only one that are underwriting these kind of credit lines, but we opened up this process also to third-party curators.

It's kind of, if you look at what happened with Morpho and other over-collateralized lending protocol in the past where they introduced this kind of curation role. That's essentially the same that we're doing with orato compared to other on-chain credit products. This allows us to have, again, more scalability for these kind of products because we're not the only one underwriting new borrowers, but we have other creators that can provide this kind of underwriting capabilities. And also in our longer term vision,

the curation-based model allows us to work also with, you know, kind of like traditional financial institution. Instead, we see more like products like maple or centrifuge, kind of an in-house underwriting company. So that's pretty much like the main difference that we have. It's an open curation-based model versus all in hours underwriting process. So underwriting is actually really skilled task, right?

So kind of like what it kind of takes is kind of you need to understand the books of this company. You need to understand the business prospects. You need to kind of, you need to calculate the default risk and the associated interest. You need to charge in order to kind of break even. Tell me how this process is handled within Pareto and kind of like how you outsource this to others. So with Pareto, that's a really good point in the sense that underwriting requires a lot of skills and also a lot of domain expertise, I would say. That's why also we started with institutional digital native funds,

So we are, which are most familiar with what we have been doing in the past. So we completely understand the kind of deployment and strategies that they're going to apply to the credit lines that they're opening. And of course, like the first step, it's pretty much like, as you mentioned, scan and review of the credit wordiness of the borrower, which is given by analyzing the books and the balance sheets of these kind of box. making sure there is enough equity, for example, to be able to cover for any losses. And I would say that there's been some experiment in underwriting in the past. I'm not talking about Pareto, but in the past, there's been some experiment in underwriting small

companies, for example, which turned out to be a bit too much naive. And so I would say that, like, in order to bootstrap and grow, this kind of credit space, we need to start with more solid corporation and institution at the beginning, just to make sure that Defi still get a good reputation on credit side. Then it really depends on the kind of deployment. For example, we work a lot with Maven 11 credit as a curator for FileConnects. And what they do is pretty much on the writing side of things for the credit line that we have. There's been a lot of work around the Covenants, that are around the credit lines.

So the borrower has a certain kind of parameters and action that they can do. And at the moment, Maven 11 is monitoring that. And we're doing the same for other borrowers like Fasanaura or Bustin trading, for example. So it takes an initial screen of the wealthiness and credit wordiness of the borrowers. And then it takes also monitoring tools and monitoring capabilities. for making sure that the healthiness of the borrower is still there. It's a bit manual at the moment, but our goal in the next, I would say, here,

is to automate that process. And actually, just to introduce a bit a new concept here, but what we see as a really interesting implementation into this kind of credit line is zero knowledge technology. because what we realized is that most of the information and data that we need to monitor and review to make sure that there is a good credit warning for a borrower are sensible data for the borrower. The borrower doesn't feel really comfortable in making this kind of information completely public, both for compliance reason but also for just to be ahead of other competitors and not to fall behind other competitors.

And what we saw is that like ZK technology really fits well in this kind of area on monitoring credit warnings and covenants for certain credit lines. So I'll give you a really, really simple example of that. Let's say that a credit line for an institutional borrower has a covenant that says that the borrower can only deploy funds into tier 1 exchanges and no more than 25% of the entire loan amount can be deployed into a single exchange. So the borrower doesn't want to expose all this kind of data for all the reason that they have. And by using ZK technology, more precisely, ZKTLS, we essentially encrypt this kind of data. And what the lenders receive is a proof of the fact

that the covenant is respected. And so also that the credit wordiness of the borrower is still there. And in this way, we also automate the process from a more traditional monthly reporting or like a certificate of collateral on a specific custodian that is issued, then you need to completely rely on a single data source. Two, the idea is to have the borrower, being able to plug in multiple data sources from centralized exchanges, custodian accounts, bank accounts even, encrypt this kind of data. So all the sensible information are protected and it's privacy preserving for your final borrower.

But the lenders on the other side are able to get a proof of the fact that the commonants are respected than the borrower credit warning is still good. Is there some sort of second opinion for the underwriting? So kind of do you have different companies kind of look at the same? same loans or kind of is the underwriter in some way incentivized or penalized if they kind of make a wrong assessment? I mean, wrong assessment goes a long way here, right? Because kind of like everyone acknowledges from the get-go that there is some level of risk and kind of in order to kind of say whether something was calculated correctly or not, kind of you would actually have to run this

experiment many times and kind of like you're only running it once. So kind of, so kind of even if kind of like there's only a 2% chance of default that is acknowledged. Kind of like those 2% can materialize, right? So kind of how do you do quality assurance on the underwriters? That's a good question because we have been thinking about this because of course, like underwriting process is not like mathematics, something that mathematically you can always be right. So of course, overall, we could.

expect defaults in the as we scale up this kind of credit protocol. So we cannot like say, no, okay, there won't be any defaults. So we need to build around mitigating also this kind of default risk. And one way, at the moment, essentially, each credit line can be curated by a single curator. So there's one entity that takes care of on the writing and monitoring the healthiness of a powerwork. But the guardrail and the essentially the protection that we embedded into it is that the curator is also a legal representative for the lenders. So it doesn't take care only of the underwriting process and monitoring process for the borrower. But in a case of a default, the curator in this case becomes the lender

represent legal representative towards the borrower. So the incentive, of course, for the curator is to make sure that they are doing the right calculation in order to get the default risk and also to make sure that they don't underestimate this kind of default risk because then they are responsible for any legal representation for the lenders, which is actually another difference from other protocols. Other protocols essentially if you are a lender and it happens to be a default, it's up to you to go to court, to file the bankruptcy, for example, documents in order to get back usually multiple years, any proceed from the liquidation of the borrowers.

Instead, in the setup that we have, is the curator that is also taking care of this process. So, of course, because of that, the curator is more incentivized to do a proper due diligence and proper monitoring of the borrower, even if it means to be more conservative than the usual process. But that's the initial incentive. Of course, this is not the final setup, I would say. Over time, for example, yeah, having multiple creators with kind of different roles, like one underwriting initially and doing due diligence,

another one doing monitoring just to have like multiple parties that provides an understanding of the borrowers makes completely sense. But yeah, at the current time, that would be the incentive for the curator to provide a proper due diligence and provide a proper underwriting process. What happens if the underwriter just doesn't do it then? So kind of like, say the borrow defaulted and kind of like there are 20 lenders that kind of now I as an underwriter meant to represent it. I just don't do it and I kind of just kind of step out of my business and let it default,

start up a new underwriting business and kind of start from square one until, because kind of defaults are kind of if you played in any way kind of correctly, defaults are rare, right? Kind of like default should be rare. So if I can run my business until the first default unfettered, am I not incentivized to do that? Yeah, I see what you're saying, but actually there would be liabilities for the underwriter as well.

So, of course, I see what you're saying, that you just close out the underwriting business on that entity and you open up a new one, but you completely destroy the reputation of your underwriting process. So these are known entities, you know who they are and kind of like there is kind of like a soft reputation, even if it's not on-chain, kind of, you know. I would say, yeah, institutional, like in the on-chain credit,

is given we work with a spectrum of collateral, because we can enable borrowers putting collateral, of course, but we can work with a full spectrum of collateral from kind of standard collateralization ratio to even zero collateral. I think it's all about reputation, like all this kind of lending is also reputation based lending.

So I see a lot of also borrowers, institutional borrowers at the moment that are looking at this kind of under collateralized credit lines as a way to build a credit score that is like it's on chain and all the interest payments that they make, all the repayments of the notion,

of the notion that they make is essentially something that builds a credit score that is on chain and it's immutable on chain. So I would say that a big part of managing these kind of credit lines is also making sure that the borrower but also the underwriters has this kind of reputation-based way of working on the credit lines. Okay. So I think we kind of cover the how and the why and kind of the what. Maybe let's look at the house. So kind of like if you could walk me through the mechanics, kind of like from the lender's deposit to kind of how the credit gets allocated

and how the yield is paid out and how often kind of these loans are novated and so on. I think kind of that would go a long way. Yeah, absolutely. So well, the process of lending, out to a specific credit line. From a UX perspective, I would say we made sure to make it as much similar to the normal DFI UX as possible. So initial, like, you know, liquidity providers could feel they were still like in DFI.

Of course, there are some compliance requirements that we need to respect depending on the jurisdiction of the borrower. So all the credit lines at the moment have. a K-YC process that you need to go through as a lender before being able to deposit. And so after that, like you can, of course, you can access all the data around the borrower or all the data around the performance of the Volt and make sure that these respect the risk reward profile that you want to have for your credit exposure. The kind of like the duration and the instance,

interest rate models of the credit lines, that really depends on the borrowers. Because as I mentioned before, we built the protocol around customizability and modularity of the credit lines. So the borrower can really decide how the interest rate model behaves and what is the duration or the covenants of the credit lines. So just to give you some example, just to let also the old. here understand, better understand how the current credit lines works.

We do have usually like weekly to monthly duration of these kind of credit lines. At the end of which the borrower needs to pay the interest rate, the lenders can request withdrawals and borrowers have like different duration from weekly to monthly to satisfy this kind of withdrawal request. And so the interest rate model, for example, it's decided to be with the underwriter, but also the borrower. So for example, Fasanara, which is one of the borrowers that we have, wanted to have flexible on chain credit line that we done interest rate

that was based on an external benchmark. So Fasanara Digital is currently running at the Delta Neutral Struct. doing a funding rate arbitrage strategy. And so they wanted to have the on-chain credit line attached to the performance of this kind of funding rate strategy. So we took a benchmark, which is the open interest-weighted BTC funding rate times 1.3, which turned out to be 88% correlated to Fasanara performance. And so we integrated this kind of interest rate model into the credit line. So that's how we can, like the customizable is really,

it's something that can be used within credit lines and really changes the way the credit lines work. For example, instead with FileConnects is pretty much traditional. It's a fixed rate facility with 30 days, callback period. So it mimics a bit more the traditional kind of credit lines that they already had. But with the advantage of now, for example, Falcon X credit line has been used as a collateral in Morpho. So lenders can also, you know, perform looping strategies on Morpho or even just, you know, use it as a collateral to borrow out to USDC

and deploy USDC somewhere else. So you bring also more capital efficiency. So the process of deploying funds is pretty similar to DFI, standard, I would say, UX apart from the KYC process. Different story also for USB and SUSP, which is the yield being stable coin that we put on top of that. But I'm going to stop here and not sure if you have other questions on the credit lines itself. Yes. You said there is Compile 3KYC. Is that just for the lender or also for the just for the borrower or also for the lender? Also for the lender, yeah.

What are the requirements on the lender here? It depends on the borrower in the sense that different jurisdictions are required different level of KOC. For example, with Falcon X, it's US-based and we do, let's say, traditional KYC process. So getting all the documentation, source of funds, corporate documentation, if it's an entity that is deploying funds into Falconex. and so I would say it's more traditional kind of KYC process. We introduced also in partnership with our KYC provider, which is Kearing, the proof of KYC way for some of the borrowers are fine with it. And essentially what we do is letting the user login into our application

via Coinbase, Binance, OKX accounts. And this allows us to hinderit the KYC level that they have on those centralized exchanges. So user doesn't have to redo again all the KYC process with this kind of KYC process that we have. But they just need to log in with Coinbase, Binance, O KX, or even we do have Revolut, for example, as a possibility to log in with. And we hinder it and we get a sort of like, of KYC. And that's for some jurisdiction enough for the borrower to be respecting the compliance requirement that they have. So those are the two current ways that we can allow lenders to KYC

and depends on the credit lines and the jurisdiction of the borrower. And are the timelines for borrowers and lenders typically different? So kind of like my naive assumption would be that as a borrower kind of I prefer longer time lines, whereas as a lender, kind of I want the, I want to be able to kind of recall my loan kind of like from week to week. Do you see this in practice? Yeah, we definitely do see that in practice. I would say it's pretty much a process of finding kind of a credit market equilibrium in the sense that we do receive requests from borrowers to have longer duration of these kind of loans and on the other side lenders ask for shorter durations in

order to be able to recall funds. What we saw is that using a marketplace approach to that so the borrower can propose different duration and let the lenders feel the credit line that they prefer to have makes sense. Of course, like the behavior that we see is that usually borrowers prefer to have longer duration, but for longer duration, they know that they have to increase the interest rate. So it's kind of like having the borrowers bidding and providing these different terms to the lenders, and then the lenders find an equilibrium and find a sort of like natural deployment into the votes that they respect, that they respect the risk reward profile and also the duration that they want.

So there is kind of a process of finding the equilibrium at the beginning where the borrower proposed different duration and different interest rate models and the lenders pick and choose the one that they prefer. And yeah, having this kind of like marketplace approach allows this, allows us to have like multiple proposals from a borrower. Lenders decide which one is better for them. And naturally then the borrowers keep the one with more liquidity into. that is being allocated into it.

Okay. You also kind of briefly touched upon this earlier, but kind of there's also this synthetic dollar product that you have. Walk us through that. Yeah. So we decided to introduce this kind of synthetic yield bearing asset into built on top of the credit lines. Because, well, on one side,

we wanted to create a sort of like index of this kind of credit lines. What we observed is that some institutional allocators wants to control their credit exposure. So they want to create their own credit allocation. And so they pick and choose different credit lines with different allocations. And that's their own decision. But some other like institutional allocators actually wants to have exposure to pretty much a diversified basket of credit lines. And they don't want to really like trigger and control all and monitor all the exposure

that they have. They're just fine with all the borrowers and they want to have exposure to all the borrowers. And so on one side, USP and SSP, which is the name of the synthetic dollar and yield-bearing synthetic dollar that we have, allows to have a basket of asset to access a basket of credit lines instead of having to pick and choose all the credit lines. And on the other side, actually, this creates a way for less sophisticated investors to access these kind of credit exposure. You can see that as a sort of like, you know, ETFs compared to pick and choose stocks and build

your own stocks portfolio. And so the way that USB and SUSP works is that you, the way that, you, the, deposit usDC or in the future USDT and USDS, for example. And these table currents get allocated across a basket of credit lines, which currently we proposed an initial allocation mechanism, which is kind of inheriting also the expertise that would build with idle finance and the yield aggregation with idle finance. But in this way, in this instance,

it takes the borrower credit boardiness, the duration of the loan, the interest rate model, it creates a diversified allocation across these kind of borrowers. And also always keeps a reserve that is highly liquid to being able to meet withdrawal request from the stable coin. And so this gives access also to a less sophisticated, but also to, I would say, a permissionless kind of audience. because having this kind of synthetic dollar

and yield-bearing synthetic dollar allows us to apply the, let's call it, Circle model. If you want to have USDC and mint or redeem USDC, you need to be K-YC, you need to go through Circle onboarding process, and then you're able to mint and redeem USDC against dollars. But you can actually acquire or sell USDC on secondary markets on Dex's, for example.

And this is something that we can apply as well to USB and SSP. So permission is the user that doesn't want to go through K-YC, that can acquire USB in uniswap, Curve Balancer, for example, stick it, and then eventually sell it back into Uniswap balancer or curve. So this allows also to broaden the audience and the access to this kind of crediting index, also to a permissionist kind of audience and not only to a permission kind of audience.

I have several follow-ups here. So the first one being kind of like a mechanical one. So seeing that I can kind of deposit into this pool anytime, kind of how do you make sure that the size of the pool is commensurate with kind of the borough volume that you see? You're saying that since you can deposit into USB whenever you want, how do we match that with the borrowing request on the other side? That's a really good question. At the current scale of USB and SSP, that's not being an issue.

So you have more borrow demand. Exactly. We do have more borrowing demand at the moment, but it's an aspect that we have been thinking about. and I think that what fits well is that we can also integrate, you know, blue-chip defy-ield sources as a way to park this kind of capital if there is not enough borrowing demand. Like, for example, deploying into S-U-SDS, so the old DSR from MakerDAO,

or into other USDA-E-S-D-C Ethereum pool, which are kind of, you know, blue cheap. Respect to the Idle Dow roots. Exactly. Exactly. Okay. Second question. Kind of previously, kind of in terms of legal defensibility. So kind of previously kind of I can see how you say, okay, we're just, we're just kind of the matchmaker here.

Kind of like this is a one-to-one relationship. But kind of like with USP, arguably, you're offering kind of an investment product, right? Are you worried about that? So the legal clarity around that still to be shaped, I would say. But yeah, we are being thinking around that. Like we don't want to completely being like investment advisors, I would say, on this kind of thing. Because of course, yeah, like we deal with aggregators. If there is a central team, a central entity that just propose the allocation.

you end up to be an investment advisor. And that's kind of borrowing a concept from what we built also with Idol Finance, which is that we, the allocation mechanism for the USDC or USDT or USDS that are backing USP, it's open. So essentially Pareto, we don't have a token live right now. it's going to be released because the governance process of Parato Dow in this case would be able

to also elect credit allocator managers. So we're not going to be the only one proposing allocation, but there would be up in idealistically speaking, a network. Your marketplace again for different investment strategies. Exactly. Exactly. That checks out. Okay. So USP, currently.

maybe I checked this morning and didn't seem terribly liquid, right? So kind of what's going on there? So kind of like what's the rate of return you're currently offering? And why is it not attractive enough for users? I would say, so we currently have around 4 million, 4, 5 million into USB. I think it's still taking a bit of time to bootstrap the liquidity over there because what we are missing, in our opinion, is the additional use cases with integrations with over-collateralized protocols or pendles.

So I would say that currently the interest rate on SUSP is around 11, 12%. And it's really like depending on the borrowers that we have. Currently we do have like three borrowers integrated within SUSP. And we need to expand that in order to make sure that we can on one side diversify the exposure more for this kind of index, but also being able to allocate to higher yields in order to become more attractive in general for the market. I would say that the major problem that we found out is to bootstrap the integrations. So being able to use SOSPS as a collateral in Morpho, Euler or AVE for example, create a more. more liquid fixed rate facility.

So, for example, in Pendle, being able to have this kind of fixed rate. And of course, I mean, we're still early in the development of SUSP, and I think we can make more, you know, we can push it more on the visibility side of things, which is something that we haven't done a lot yet, but because we wanted to have all the infrastructure ready

and tested out and bottle test it out, and bottle tested, I would say. So I would say it's not really about the interest rate. Because if you look at, I would say, Athena, for example, what is right now, Athena should be around like 5, 6%. If I remember correctly, they are overly allocated also to like USDS. So it should be quite similar to the SSR rate. So it should be around that.

So we're kind of like we're giving double of the interest rate of that. So I don't see the interest rate as a major problem. I see more like being able to integrate the USB and SOSP across other protocols, which is something that we're doing. We started with Euler a couple of weeks ago and bootstrapping that. We're going to push with more for getting things listed as collateral as it's a pain. Yeah, yeah, it is. But I mean, it makes sense.

It should be kind of like a- It should be a pain. Exactly, exactly. Otherwise, it's hiring the risk for DFA in general. But also like pushing on visibility and education, it's something that we're going to do in the next month, which would be helpful to understand what is USP, what is USP, where the yield is coming from.

And these we expect will bring also more liquidity and more scale to the to USP and SUSP. Okay. Credit in some sense is more opaque than most defy activity, right? Because kind of like it heavily depends on off-chain books that you don't necessarily have access to as user. How do you make this compatible or do you make this compatible with the real time transparency that people expect from Defi? That's a great point. And so currently it's difficult to make this kind of process really like comparable to the real-time automation and monitoring of defy.

But we need to go there. I mean, that's like we need to improve from, you know, traditional loan that often rely on, you know, quarterly, monthly reports to verify borough health. And, you know, this creates also a risk lag because, you know, you might find out that, find out too late that a covenant was breached, for example. So, yeah, like ZKTLS, implementing ZKTLS would be the first step towards that, towards a more automated monitoring process. and also being able to have a diversified access to different data sources from the borrower

allows us to like verify from multiple data sources that the borrower health is there compared to just a single like data source or a single auditor that makes the the auditing process on the borrower. So I would say that one of the current implementation that we have in mind to solve this is to create a sort of like this kind of ZKTLS model where the barware can attach multiple data sources with different even like frequency of data but like to try to be as close to the real time monitoring process that we have in DFI. And so like monitoring and automated.

in this process for the borrower so they don't have to provide manual reports and monthly or quarterly reports. It's kind of a step towards going close to the real-time monitoring that we have in the different. Yeah. So my worry is primarily

about malicious behavior. So I do agree that kind of all kinds of unfortunate business consequences and so on, I think kind of like, this is well-cooked by this. I'm not a finance person, but kind of, I know that kind of like if I needed to kind of make books look good, depending on kind of like, I would book things different ways or kind of like,

I would delay the booking. I think there's different ways of kind of fudging the books, right? So that kind of crisis is not immediately apparent. Do you have any guardrails against truly malicious? borrow behavior? Yeah, I would say not relying solely on proprietary data sources. So I would say like getting financial statements, bank record, the trading activities in general to form this kind of borrower reputation shouldn't be something that a borrower itself

is providing, but it's something that we fetch from data sources that are third parties. For example, it's a read-only API from a checks account. So the borrower itself cannot really like manipulate this kind of data. It would be checks that should be manipulated. Of course, there's an assumption of trust. But they can open a second account, right? So kind of like I can have one clean finance account and open a second account in the same name, right? Yeah, but when you're opening this kind of credit line, you're attaching like the either

like all the funds that you are borrowing out from the credit line should be verified that goes to that specific checks account and all the activity around that checks account is what we are monitoring. So the collateral that you're using, the kind of trading activity that you're doing from that account is what matter for the lender. So I would say these kind of like credit line should. should be getting a mix between other accounts, but should be related to a specific checks account from the borrower side.

And in general, like the way that we are also structuring from a, I would say, legal perspective, the credit lines is that they're SPV-based. So they're also bankruptcy remote from the, let's say, main company as well. Okay. So that's... So you're trying to ring fend as much. as possible. Exactly. Exactly. So if the Pareto interface and kind of like the centralized entities behind it kind of disappeared this afternoon, could I still unwind my loan or redeem my USP just by interacting

with smart contracts? Or do I kind of rely on you guys to kind of provide this service to me? No, it would be possible. The way that we made the protocol itself, especially on USP and USP side, is that there can be a way for the DAO itself to change, for example, the admin controls for the allocation mechanism, for example. That also allows to, let's say, we call back all the borrowers, all the funds from the borrowers and repay all the USB token holders. So if we call it, we have been called it in this kind of test, with our legal advisor

the Bahamas test. So if all the team decide to go to Bahamas and just don't build the protocol anymore, we need to have a way to let the community and the token holders to be able to change the parameters and to change the admin controls,

recall all the borrow, all the loans and we pay back the, and we pay back USP and USP. So yeah, we have been thinking about that and since the beginning, the protocol is made to be open in a way that it doesn't only rely on the core team. Maybe as a closing question, if you look at the on-chain private credit market and Pareto in particular,

what does success for you guys look like in the next two to three years? Nice, great question in the sense that, of course, the main metric that we're using in DFI is So that's kind of an R-star for all the DFI projects. And that's what we need to, what we're focused on growing over time. And that comes, of course, from creating a more and more diversified market in marketplace. So what I see as a growth to driver and potential expansion for Pareto in the next two, three years, I would say, is to gradually introduce non-crypto-related borrowers. We want to have a way to give away us to lenders and liquidity providers in general to not rely only on borrowers that are related to the

crypto market because then depending on the market cycle, you're completely subject to the market cycle. And so the first driver would be to expand into more corporate bonds, corporate loans, of credit lines. So introducing kind of like fintech companies or cross-border payment facilities, credit card companies, account receivable companies, still related to finance and fintech, but that would be the first expansion. And so creating this kind of more and more diversified marketplace that would allow also to grow USB and SSP diversification power and allow also to work with a larger basket of borrowers, barrage capabilities and loans in general,

to grow also USP and SUSP. So I would say two, three years, we onboard new kind of corporate borrowers. We onboard new curators that in our vision are also like traditional institutions that bring their own underwriting process and due diligence process on chain without having to build everything from scratch.

And of course, that would be like meaning a TVL that goes above one billion to like numbers that were more. Like, you know, creating market is a 15 trillion market all around the world. So we do have a lot of room of expansion here in DFI. So like our first like Meistone is one billion of TVL, but then we need to think bigger with like this kind of number and we need to grow from there. Cool. Mateo, where do we send people to find

to find out more about Pareto and kind of potentially borrow and some money with you guys? I would say let's definitely direct users and the audience that is interested to learn more about Pareto to Pareto. that would be the main point of access where you can access the dashboard.

So you can see all the bolts, read about the borrowers that we have, read about the strategies that they're running, and understand more also about USP and USP. And then I would say if they want to also keep up with the announcement that we're making, which lately are a lot, actually, to follow us on Twitter at Pareto.comcredit. You can find all the links at Pareto.orgredit for Twitter as well to look at all the announcement that we're making and also to read the blog post

and the articles that we made with our partners. Perfect. Thank you so much for. coming on, Mateo. It's been a pleasure chatting with you. Thank you. Likewise.