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TOKENFUTURE Preview: How Untangled Wants to Transform Private Credit

"Ultimately, tokenized private credit will foster greater financial inclusion."

Untangled Finance is one of the most promising startups in the Real-World Asset sector. Through their collaboration with Fasanara, granting access to over 140 vetted originators, and leveraging their credit oracle infrastructure, Credio, the team aims to revolutionize onchain capital markets, thereby opening the $1.5 trillion market to a broader range of investors.

At next week's TOKENFUTURE, Manrui, along with her co-founder Quan Le, will share unique insights from the forefront of RWA innovation and unveil exciting details about Credio, Untangled's oracle infrastructure designed to accelerate the institutional adoption of on-chain private credit.

In preparation for her appearance, we interviewed Manrui and went deep into the following topics:

  • The current state of the onchain private credit market

  • Main obstacles for the adoption of tokenized private credit

  • How Untangled's Credio will transform the RWA sector

  • What the future holds for Untangled

So, without further ado, please enjoy my interview with Manrui Tang.

The State of Onchain Private Credit

Can you explain what people mean by private credit, including the types of collateral and stakeholders involved, and the market size? Why is bringing private credit capabilities onchain beneficial?

In short, the term private credit describes loans which are made by lenders other than banks, such as private equity firms, hedge funds, and other private lending institutions. Typically, those loans are given out to small and medium-sized businesses.

In the past decade, the private credit market has grown rapidly and reached a size of around $1.5 trillion. Besides stricter banking regulations post-2008 financial crisis, this growth was fueled by investors seeking higher yield opportunities.

As with other industries and use cases, tokenization drastically improves the cost-efficiency of private credit operations, primarily by reducing the associated costs. In addition to that, due to the open nature of decentralized finance, onchain private credit markets can be accessed by a broader set of investors.

This means that the privilege of participating in those deals opens up to accredited investors as well - instead of being reserved only for institutional lenders.

Many people might have heard already about protocols like Centrifuge or Goldfinch. What is the current market landscape for onchain private credit, and how well have existing protocols been adopted?

The current market landscape for onchain private credit is relatively small, with a market size of around $500 million.

But it used to be a lot higher than that.

When the total market size was well above $1 billion in March 2022 - around $1.3 billion if I remember correctly - the FED started its aggressive tightening cycle, shifting investors’ preference away from private credit investments towards the safer U.S. treasury bills.

This is also when many DeFi protocols started to focus on tokenizing T-bills, gradually moving away from the onchain credit market. One of them was MakerDAO, a major investor in real-world assets (RWA), which has stopped using private credit collateral for issuing its DAI stablecoin.

Although the complexities and risks associated with onchain private credit are a bit higher compared to the tokenization of T-bills, we are certain that once the interest rate cuts begin, yield-seeking investors might take another look at the sector.

Biggest Obstacles to Broader Adoption

Apart from macroeconomic factors, what are the main obstacles to the adoption of tokenized private credit?

Historically, the main challenges have been low asset quality and liquidity issues, which make it difficult for investors to exit their positions at will. During the strong growth of DeFi in the last market cycle, the influx of new capital attracted lower-quality collaterals, often from borrowers who were overlooked by traditional finance.

Combined with inadequate due diligence and pricing mechanisms, as well as inflated returns driven by token incentives, this ultimately exposed investors to risks similar to equity stakes.

Additionally, once investments were made, there was a lack of sufficient onchain monitoring, leaving investors unaware of problems until they became severe.

Furthermore, the absence of a robust legal framework to protect investors' interests meant that defaults could and partially did result in total losses.

Untangled Credio - Credit Oracle Network

You’ve been working on decentralizing credit pricing with a new oracle network called Untangled Credio. What motivated this initiative, and what is Credio about?

Credio aims to decentralize credit modeling and asset pricing by allowing experts and major rating agencies to provide credit prices to RWA lending protocols. Additionally, we want to leverage AI-driven risk models and zero-knowledge cryptography to enhance the accuracy and reliability of credit pricing and monitoring.

Why is this so important?

In traditional collateralized lending, determining the value of collateral is crucial as it directly impacts the loan's recoverability. For instance, if the collateral ratio (value of collateral/loan amount) falls below a certain threshold - typically 150% to 110% - the collateral is liquidated to repay the loan. For this purpose, DeFi lending protocols like Aave and Compound rely on price oracles such as Chainlink, which provide them with real-time price feeds.

However, the most utilized collaterals inside those protocols are crypto-native assets like ETH or BTC, which have deep markets and therefore plenty of price data. In contrast, RWA lending protocols face greater challenges in valuing collateral, mainly due to the lack of liquid on-chain or secondary markets with easily observable prices. Instead, they need to adopt a 'fair value' approach using statistical or machine learning models to estimate prices or default probabilities for credit collaterals.

This inability to reliably value and monitor collaterals has consequently led to defaults in many RWA lending protocols.

Credit modeling is another pain point. Whereas in traditional finance (TradFi), credit modeling is handled by rating agencies like Moody’s, S&P, and Fitch, DeFi still lacks such mechanisms and ‘data infrastructure’.

Those are all the problems that we try to solve with Credio.

As of now, the only asset pools powered by Credio are deployed on Untangled. This allows us to provide better and most importantly safer investment opportunities compared to similar offerings.

Who are the key stakeholders in this network? 

The whole system can be split up in three distinct parties:

  1. Consumers: These include smart contracts/dApps and individual consumers that use machine learning predictions for risk parameters, credit ratings, or risk scoring. In practical applications, they might be issuers needing credit ratings, investors updating credit prices for their portfolios, or smart contract protocols calculating the net asset value of their holdings.

  2. Modelers: These participants tackle ML challenges to develop predictive models, such as credit ratings or scoring, that meet specified performance standards. They also provide zero-knowledge proofs along with model inferences/outputs. These participants include global rating agencies, RWA risk managers, and data scientists with expertise in specific asset classes.

  3. Validators: Validators play a critical role in securing the network. They ensure that the models meet performance benchmarks, verify proofs, and validate off-chain data inputs into models.

How do you ensure the validity of both the inputs and outputs in the computation process for deriving credit assessments?

Great question!

To ensure validity, we employ several robust mechanisms:

  • Zero-Knowledge Proof Technology: Modelers must submit zero-knowledge proofs alongside their model outputs. This makes it possible to verify that the outputs are correctly derived from the inputs, all while keeping the model's internal processes confidential, and maintaining the model's privacy.

  • Smart Contract Verification: Before any smart contracts are updated with new risk prices or parameters, Credio verifies the validity of the provided proofs. We collaborate with Chainlink's automation technology to ensure accurate and reliable updates.

  • Validator (Dis)Incentives: Validators ensure the security of machine learning challenges by verifying submissions and monitoring ongoing operations. They are motivated to act diligently and responsibly by the risk of slashing penalties for any failures or misconduct.

Together, those building blocks ensure accurate and trustworthy credit risk assessments on our network.

Zooming out again: Why is an oracle network like Credio significant? What are the broader use cases and potential opportunities for the financial industry?

As previously mentioned, real-world asset (RWA) collaterals involve substantial credit and counterparty risks, which have hampered the growth of RWA DeFi due to issues like bad debts and non-performing counterparties.

Currently, there are no oracle solutions for illiquid RWAs. Furthermore, even liquid collaterals such as tokenized treasuries face counterparty risks, leading to inconsistencies in returns for products based on the same underlying assets. Without a system like Credio that provides risk pricing and monitoring of tokenized RWAs, large-scale institutional participation will likely remain difficult.

Credio helps to accelerate the adoption of onchain private credit markets to achieve greater efficiency in today’s financial markets.

What's next for Untangled.Finance?

What are Untangled’s key milestones and goals in the near future, and how do you plan to build out the network?

Our priority is to bring institutional-grade private credits to DeFi by collaborating with our institutional partners and continuing to develop the on-chain securitization markets. With Credio, we aim to work across the entire RWA DeFi space, addressing various asset classes.

To further build out the network, we are actively forming partnerships with rating agencies, risk managers, and data scientists from our core partnership group. This collaborative approach will help us establish a robust and decentralized ecosystem for managing and pricing credit risks in the DeFi space.

In five years, what impact do you believe the tokenization of private credit will have on traditional credit markets?

At Untangled, we believe that a substantial portion of RWA financing will either be tokenized or natively originated on-chain. We anticipate that tokenized private credit will enhance transparency, efficiency, and accessibility in the credit markets, ultimately fostering greater financial inclusion.

Thank you very much, Manrui! Really looking forward to seeing you at TOKENFUTURE!


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