In this third community call and AMA session, the Atlendis Labs team was pleased to welcome special guests Charlotte Eli, Co-Founder and Chief Research Officer of Atlendis Labs, and Darshan Vaidya, CEO of X-Margin. X-Margin specializes in proving creditworthiness of borrowers by evaluating their exposure. This was an opportunity to learn more about the nature of the partnership between Atlendis Labs and X-Margin, find out how credit scoring is handled in Web3, and more specifically, how it comes into play for the whitelisting and creditworthiness assessment of borrowers on the Atlendis protocol.
This article is the written transcript of the following audio, available on Atlendis’ YouTube channel:
Let’s get started and wish a warm welcome to Charlotte. Hi Charlotte!
Charlotte: Hello everyone! It’s a pleasure to be here today and interact with the Atlendis community!
Charlotte, before we get started, could you tell us a little bit about your background and your role at Atlendis Labs?
Charlotte: Sure, I’m Charlotte, one of the four Co-Founders of Atlendis Labs, and I’m also our Chief Research Officer. I have a background in Financial Mathematics and Data Science. I worked as a Quant in TradFi in a previous life and I moved to the crypto space in 2017 when I joined ConsenSys and worked as a Financial Research Engineer.
As Atlendis Labs’ Chief Research Officer, I am responsible for defining the financial aspects of the Atlendis protocol. This includes, contributing to the whitepaper that defines the financial specifications, and developing a simulation engine, as well as a testing framework that ensures the financial specifications are in line with the implementation.
Thank you Charlotte. Now let’s give you, Darshan, a warm welcome! Thank you so much for accepting the invitation and being our guest today. Let’s start with the same question: so could you briefly introduce yourself and share a bit about your background?
Darshan: Yes, sure! Thanks so much to the Atlendis community for having me and it’s a pleasure to partner with Atlendis. My background is much like a lot of people in the crypto space. I started in traditional finance, was an options trader for a long time, and was one of the early market makers and options traders on Deribit, which is now the largest options platform in crypto. Basically at that time the credit space was very nascent, more so than today, and we struggled as a fund to scale the book because we weren’t able to access capital from lenders. Back then it was difficult to borrow uncollateralized, and it led me down a rabbithole and we built X-Margin really trying to prove creditworthiness to someone without having to share sensitive information with anyone. So that’s what led me to start X-Margin and I’m one of the co-founders.
Thank you both for the introduction. Let’s start with you Darshan, could you tell us how your adventure started with X-Margin?
Darshan: It’s quite difficult to scale a market making book without access to capital. You’re generally buying on one exchange and selling on another one, trying to balance your book as easily as possible. You’re a natural borrower of capital. Usually in traditional finance, you have these credit intermediaries like primes or banks, and you access the market through them and they evaluate the credit worthiness of your firm by seeing all the trades that you’re doing and they tend to be your sole safe source of credit. Inherently it’s not like a competitive credit market, they take a big spread, to do all of that internalizing of credit risk. They borrow quite cheaply and then essentially lend to you at whatever rate they feel appropriate, but they take a large spread as a result. And so, credit markets as a whole work like this as well, where you have this trusted intermediary who sees all the data, there is this opaque credit process, then you charge a fee or capture a really large spread to internalize all that credit risk. So credit evaluation is generally done intermittently, not in real-time and is usually not able to keep in touch with moving conditions or moving creditworthiness, for example, if someone’s behavior changes, or if an institution’s risk may have changed.
Our goal is to do the opposite of this, and look at credit from a completely different perspective. We guarantee the data privacy of the borrowers, we do real-time analysis of that data and we keep the methodologies open. Then we compute on all this data in a completely private and neutral way backed up by cryptographic proofs. Then we guarantee the data privacy of the borrower and that data makes credit much more transparent and competitive. We leverage this privacy preserving technology to do these computations and ensure that we‘re this provably neutral and private arbitrator of someone’s risk and as a result, disintermediate credit warehouses that traditionally have made credit markets less efficient and less accessible to a large portion of individuals.
Thanks a lot, very interesting. One precision though, is X-Margin only navigating in Web3 or also working with non crypto-native companies?
Darshan: The crypto space was the first space we tackled as the demand for credit was so acute, the ability to access credit is quite limited, but this is just one of those instances where the technology and the tech stack built with the crypto ethos can actually be used in the real world. We currently pull in information from someone’s CeFi or DeFi exposure and compute on that in a private and real-time way. But there’s no reason it can’t be for example, Stripe or Shopify, or some banking APIs, and really with any credit methodology that could facilitate credit to non-crypto firms and even individuals.
Okay, a question for Charlotte now. Why did Atlendis Labs choose to partner with X-Margin?
Charlotte: We decided to partner with X-Margin, as we believe that credit-scoring is a key element to enable lenders to properly assess the creditworthiness of the borrowers. We chose X-Margin, as they are a leading player in credit evaluation in Web3, with the expertise to provide real-time credit scores. The fact that they are able to evaluate both on-chain activities, and traditional financial data was a key element for us.
We also needed a partner that was able to evaluate both crypto-native and, in the long run, non-crypto native entities, so that we could give the opportunity to our lenders to diversify their portfolios.
What are the main services currently provided to Atlendis by X-Margin?
Darshan: Yes, of course. I’d say our credit evaluation is broken into three main components: due diligence and KYC component, we look at static data (financials) and real-time risk monitoring. From these components, we can then calculate a credit score, which is continuously updating and can also estimate from these components the general size of someone’s balance sheet and approximate borrow capacity, so it’s an estimate of their overall borrowing appetite or ability based on that credit score and size of the firm.
This provides users of the platform transparency of the risk of all the borrowers there and allows for secondary markets to be created on any credit as well. If that credit score is constantly evolving, it allows someone to evaluate whether they want to lend more, whether they want to recall or sell the loan to someone else. We believe that real-time data can supplement significantly the other components.
How is the partnership between X-Margin and Atlendis different from what X-Margin is doing with other protocols?
Darshan: While our goal is for our oracle to be universal and consistent across platforms, it takes into account for each platform the business types and the different ethos to credit facilitation. So far Atlendis borrower client types are very diverse. We have so far been previously focused on trading firms, but now we are expanding that to lenders, DAOs, crypto native start ups and much more in the pipeline. I think on the Atlendis side there is more of a traditional price discovery on the platform, as opposed to an intermediary deciding what the price of the loan is or some pre programmed curve, there is more of a marketplace for what that rate should be and we feel that our data is super important for that, and to be able to reevaluate what that price should be and whether the demand for a loan is going up or down, based on that creditworthiness. So there are some really natural synergies there with our data.
How will Atlendis make use of X-Margin’s data, and how will that help borrowers access uncollateralized loans?
Darshan: The way Atlendis will use the data is to make borrower risk as transparent as possible, but maintain the privacy of the sensitive information of that borrower. Inherently in someone’s creditworthiness, the data that goes into someone’s credit worthiness analysis is generally private. On the whole, that gives you the best insight into someone’s creditworthiness. Being able to do that analysis in real-time and privately, we’re able to create transparency but preserve privacy. So it’s easier and more efficient to discover the price of any loans. For the borrowers, there is a more competitive landscape for that credit as a result it encourages more entrants from the lenders side into the credit market, and allows them to tap into more than the current sources of capital. They’re able to build up a credit score and a profile, and lenders can then create secondary markets around that credit extension. I think those are the main things we can bring to both sides of the market.
From your perspective Charlotte, how can lenders benefit from X-Margin’s integration with the Atlendis protocol?
Charlotte: On the Atlendis protocol, lenders have full ownership of their portfolio. They can individually choose their borrowers, and they can select their preferred lending rate, based on their own risk assessment and their investment profile.
With ownership, comes a lot of responsibility so X-Margin’s credit score will be displayed on the Atlendis dApp, and will be used by lenders, to decide whether or not to offer credit, and at what rate. Also, as X-Margin credit scores are updated in real-time, existing lenders have the ability to adjust their lending rate, in the case of a credit score update.
Would you like to add something to this Darshan? How can Lenders benefit from X-Margin’s integration with the Atlendis protocol?
Darshan: I’d say if you look at how lending today happens in the crypto space, a lot of it is based on trust and reputation. We’re really trying to move away from that towards a more data driven approach. As I mentioned, the creditworthiness data that generally provides the best picture of someone’s creditworthiness is private, but it means an intermediary has to be involved to check that data. Another option to evaluate that data in a disintermediated way is if you had a consensus mechanism for example, but obviously that’s not possible when you’re handling private data. What we’re doing is this middle ground using private computation but still able to disintermediate this credit warehouse without needing a consensus mechanism. What that means for lenders is having this transparent, real-time creditworthiness picture, and unparalleled levels of information on what a borrower’s risk is. It allows them to access lending markets without this intermediary that generally takes a spread for doing that data analysis themselves.
Well since we’re on that topic, we’d be interested in having your take on the recent events in financial markets at large and specifically in the crypto space. How do you think our technologies can help prevent recent events or help markets recover from the aftermath?
Darshan: Recent market events have taught us that tail risk must be respected, and that someone’s creditworthiness can really evaporate overnight. As a result, real-time risk monitoring is more vital than ever, and the ability to track a borrowers’ liquidity and risk in turbulent markets becomes crucial. It allows for a push for more regulatory sound and risk-managed processes. How lenders may have reacted in the recent market downturn, a lot of them would have wanted to know how creditworthy their borrowers were and maybe they couldn’t get that information in real-time. They may have recalled loans or may have been much more cautious about issuing loans. But if a borrower could display their creditworthiness in real-time, and can do so in this provably neutral and private way, our thesis and what we see playing out with some of our clients, is actually that they can access more capital and lenders feel more comfortable to lend to specific borrowers that are actually doing that. I think that the technologies we are both working on, can enable more credit in turbulent times by being transparent about the risk.
From your side of the industry, what recommendations would you give to protocols seeking to avoid the mistakes that lead to the recent crash, hedge their counterparty risk and eventually protect their users?
Darshan: I think there are many lessons to be learned about tokenomics, protocol design and incentives that are important, but that is perhaps outside of the scope of what we are working on.
But, two main lessons that we believe are important and relevant here are to focus on sustainable yields and not depending all growth on rewards. This can allow for a more sustainable ecosystem. And then transparency of risk, making that risk available in real-time and transparent to lenders can prevent a spiral of capital being drawn out. That risk calculation has to factor in tail risk as well, and this is something that we have been championing the whole time we’ve been around.
Super clear and interesting, thank you Darshan. Back to you Charlotte. Let’s continue with the whitelisting process on Atlendis. Has Atlendis already whitelisted institutions and if so, what factors are being considered when whitelisting a borrower and their wallet(s)?
Charlotte: That’s a great question Manuel! Only institutional borrowers have the ability to be whitelisted on the Atlendis protocol. They can be Web3 companies, as well non-crypto native companies, enabling lenders to diversify their portfolio. In any case, the borrowers need to have a proper legal entity.
Atlendis starts by going through a first assessment of the borrowing candidate, in order to evaluate the team, their track record, and the established business.
The next major step, is to go through a credit scoring process. The creditworthiness assessment is done by our partner, X-Margin.
Then, the borrower has to choose the parameters of their pool: the asset, their credit limit, the minimum and maximum rate, the liquidity reward rate, etc.
The decision to whitelist the borrower is based on all the previous steps that I just mentioned. The process is currently centralized, and is done by the core team, but in the future, it will be carried out on-chain, by the Atlendis community.
Darshan, how does a credit evaluation of a Borrower work? What are the steps involved on the X-Margin side?
Darshan: There are three main steps a borrower goes through when going through credit evaluation. First are performed a due diligence and KYC, which are generally requested by most lenders in the space to make sure that from an AML and KYC perspective, the borrower is legally sound and that there is enough recourse in the event of a borrower not being able to repay the loan.
Second, we look at the static information of a company’s financials, looking at their balance sheet, outstanding loans and developing a credit picture for a point in time.
Third, we use real-time data to see how the entity is behaving over time.
We believe that these three aspects combined, and especially that third one, provide a unique, most accurate and up to date form of evaluation of a borrower.
How is default risk evaluated “under the hood” by X-Margin?
Darshan: What the system is able to do is that it connects with exchange accounts and pulls in real time risk across exchanges, custody solutions, on-chain wallets, real-time risk across exchanges, custody solutions, on-chain wallets, DeFi positions in EVM compatible blockchains and on Solana, and some bank accounts.
All of this data is then pulled inside secured enclaves that do privacy preserving computations. This data is pulled in in an encrypted form and can only be computed upon inside these enclaves. Then we have cryptographic proofs that wrap around these enclaves and confirm both the privacy and the accuracy of the computation. So these nodes can only do private computations, can’t leak any data and can only do the computations agreed upon, so as a result it becomes this provably neutral real-time assessment of a client’s data across both CeFi and DeFi.
So we’re scalable across multiple blockchains and the technology allows for us to provide a comprehensive and secure evaluations for crypto firms and beyond.
What are the next steps of the partnership?
Charlotte: Next on the Atlendis protocol roadmap, is the development of meta-pools, that will enable lending to multiple borrowers. Meta-pools will be for lenders, who would prefer to have a more passive investment style. Having pools, for example, based on X-Margin’s credit score within a certain range, or pools managed by X-Margin, would be a natural next step for our partnership.
Could you be more specific about “managing” the pool? What would X-Margin’s role be with regards to meta-pools?
Charlotte: Yes, sure, well, X-Margin could act as a pool’s delegate on some of our meta-pools. They would be in charge of selecting the borrowers, and the lending rate, so that the lenders who do not wish to select the borrowers individually, could get exposure to multiple borrowers, by trusting X-Margin’s investment decision.
Darshan, are there any further developments/new features of your product in progress that you could share with us?
Darshan: Sure! I mean we’re always building and looking for ways to improve the system and of course we’re always hiring. Our upcoming feature releases are focused on making the platform more dynamic, so we’re launching updates and improvements to our credit evaluation process. I think as we get more feedback and we’re used across more protocols and lenders, we learn a bit more about what’s the right credit scoring methodology and we’re very transparent about our metrics and our methodology. So we continue to improve that credit scoring method and then really we’re trying to add more data sources to the mix. Like I mentioned, maybe pulling in from various bank account APIs that we don’t cover today, or DeFi protocols and exchanges that we may not cover today. Also looking at other borrower types outside of crypto, whether it be like a real estate firm or whether it be a small business that has like a SAS revenue that we can capture via API. So I think things like that are improving the power of this credit oracle, and then we’re working on decentralizing architecture. We currently run some of the nodes and we’re working with other people to run some of these nodes and as we grow and scale we hope to allow anyone really to run these nodes in a provably private way and add to this oracle in the way that I just described.
Thank you! Charlotte, what’s next for Atlendis in the coming months?
Charlotte: We are currently focused on our launch that will happen in the coming weeks. We have opened a testnet environment to let the first users experiment with the protocol, and give us feedback. We are already working on the future, and updated versions of the Atlendis protocol and have a lot of exciting events coming up, so be sure to stay tuned!
Charlotte and Darshan do you have anything else to add to wrap up?
Darshan: Thank you for having me, we are excited to be working with Atlentis to create open and transparent credit markets, and help build a system that has sustainably high yields with well managed risks. We’re really looking to build a private and neutral credit oracle, unlocking all sorts of different types of credit, so we’re excited to work with Atlendis on that mission. Finally, X-Margin is hiring, so don’t hesitate to reach out if you’re looking for a new opportunity. You can go to our main website xmargin.io to find open positions.
Charlotte: Well, first of all, thank you so much for putting this together Manuel, and Darshan, thank you again for joining me today! We are very excited about the partnership. I also wanted to take this opportunity to tell everyone that the Atlendis Team will be at EthCC in Paris this July, so don’t hesitate to ping us if you’d like to meet in person. And thanks again to the Atlendis community and see you soon!
Special thanks to Charlotte from Atlendis Labs and Darshan from X-Margin for speaking with the Atlendis community. Don’t miss the next community call and join Atlendis’ Discord to vote for the next one’s topic and guests. Alternatively, you can follow Atlendis on Twitter to receive the latest news and be informed of the launch.
See you soon in the Atlendis World!
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