Privacy, Credit, and Decentralized Identifier: Reflections After the Bank Run Craze

Recently, the market has experienced a series of liquidations. The demand in the following sectors may show an upward trend due to the revealed flaws: privacy, credit, decentralized identifier, and reputation systems. This article attempts to analyze the narrative potential of individual projects by providing examples.

1. The Importance of Privacy Needs

Although blockchain uses complex numbers and addresses to represent accounts, it is still possible to discover the identification behind the accounts through continuous tracking and analysis. There are many data analysis tools on the market to identify whales. To some extent, blockchain does not truly protect privacy. When an account address is investigated and found to belong to someone, all transaction data will be completely transparent.

Zero-knowledge proof technology was discovered in the 1980s, but it was not truly applied until the emergence of Zcash in 2016. Zcash offers two types of addresses: protected privacy address (Z) and transparent address (T). Z addresses are not visible, and their transactions do not display related addresses, amounts, or encrypted notes. T addresses can be viewed in public browsers. The two types of addresses can trade with each other, forming a process of free choice.

However, Zcash has a flaw in the trust issue of generating the master key. Therefore, we need to find a clear privacy needs group. Any privacy solution must ensure that both atomic components, the dApp users and smart contracts, are private and secure.

Privacy requires not only simple transaction or behavioral anonymity but also the establishment of a larger ecosystem, including various privacy applications to serve users. For instance, a large whale or market maker, in the process of real transactions, may adopt multiple strategic operations to ensure risk exposure, but currently, these actions cannot meet their privacy needs.

Therefore, privacy requires a large framework and system, based on which applications are developed and created. Aleo not only achieves asset transfer anonymity based on Zcash, but also includes payments, liquidity provision, governance voting, identification, and more. Only the interacting parties know the details, and malicious third parties cannot understand any details or exploit them.

Aleo is a platform for fully private applications, with the core still being ZKP, but providing a full-stack solution that allows ZK to have programmability at every layer of the stack, thus enabling large-scale decentralized private computation. For the two atomic components of users and transactions, Aleo ensures that no identification information is leaked.

Aleo supports composable and private applications, and provides a new programming language framework called "Leo". "Leo" emphasizes readability and ease of use, resembling traditional programming language frameworks, abstracting low-level cryptographic concepts, and is very developer-friendly.

Aleo adopts a system called ZEXE, which generates proofs during the execution of state transitions and bundles them into on-chain transactions. Transactions update the system state by creating on-chain records, so that ultimately this transaction contains only the proof and not the input of the proof. Aleo names the concealed process "zkCloud"; it is a component of the Aleo stack.

"zkCloud" enables programmed interactions between protected identities, which can be users, organizations, DAOs, etc. This computational model can run locally or be delegated to specialized validators.

In addition, Aztec, which also uses ZKP, is good as well; Aztec will address the privacy needs of Ethereum, along with Secret Network that uses TEE. Since using ZKP requires less trust, projects that adopt TEE may develop faster in comparison.

2. Challenges and Opportunities of On-Chain Lending

On-chain lending is still in the early stages of the market, lacking a large amount of middleware and infrastructure, and some issues may need to be solved modularly, such as regulatory licensing permits, mature DID systems, reasonable on-chain credit algorithm models, etc.

The core of credit lies in the construction of the credit system and the interest rates and qualifications that borrowers can afford to pay. The construction of the credit system cannot be separated from how on-chain and off-chain should coexist. DID products have been exploring how to combine or choose between on-chain and off-chain, and they are still trying to datafy and structure identity as much as possible. However, given the limited metrics and standards that have already emerged in the market, DID has not yet seen a product with a relatively high adoption rate.

Therefore, the current construction of the credit system in credit business is more about off-chain assessment. Off-chain assessment means that the assessment model is a black box, and encrypted credit is still a fragile business line.

We differentiate the credit assessment methods of the three protocols/products: Maple Finance, Truefi, and Goldfinch.

Maple Finance has introduced the delegated liquidity pool (Pool DeleGate) to introduce and evaluate loans, with each lending pool potentially represented by different pools for introduction and evaluation. The collateral rate they provide for borrowers is 0-50%, with the main clients being crypto-native institutions.

Maple Finance allows Pool Delegates to negotiate loan terms with borrowers, such as interest rates, maturity dates, and collateral ratios.

TrueFi has chosen a DAO-centric approach for voting, evaluating that the community initially sets all terms for each loan. In addition, borrowers must also obtain individual approval from holders of $stkTRU. Each loan request requires an approval rate of over 80%.

Goldfinch chooses to use third-party partner teams for the audit and evaluation of ( Personal or Parallel Markets ). Borrowers need to stake their tokens $GFI, which requires about double the cost. Then, they must submit the institution's credit report and financial statements to this team. After a successful audit, the borrower will receive a non-transferable, unique identification ( UID ) NFT linked to their designated wallet to prevent witch attacks. Subsequently, the system will randomly select 6 out of 9 auditors to approve the loan.

From an overall design perspective, the biggest difference among the three is in the evaluation method for loans. However, they all share the commonality of relying on a centralized person/team for credit assessment. Even though it includes interests of token holders, there remains confusion and uncertainty regarding the debts of those super whales.

The reputation and credit risk scoring on the blockchain are major challenges, and credit requires endorsement from strong governments, state machinery, or legal terms; credit does not arise out of thin air.

So why are there still so many emerging collateral rate models and credit assessment models in the crypto market, leading to such chaos? The root cause may lie in the fact that no one can promise what will happen if they can't pay back the money, and similarly, no one dares to bet on what will happen if they do pay it back.

At the same time, due to the large interest rate spread between DeFi and traditional banks, it has resulted in a situation where borrowers are reluctant to pay higher interest rates. ( If borrowers willing to pay high interest rates are likely to have poor qualifications, there is a certain level of risk involved ), forcing Maple and Truefi to use their own tokens for subsidy incentives. Therefore, the institutional lending business on the chain is still in a stage of striving to find PMF.

But when debt is restructured, new cycles will also emerge. Credit remains one of the DeFi driving factors that cannot be ignored.

We just mentioned that there is a large interest rate spread between DeFi and traditional banks, and the interest rate spread creates borrowing demand. However, borrowing assets simultaneously means you're short, to be precise, it implies that you have a certain implicit awareness and thought of shorting, or believe that its price may be in a state of fluctuation in a short period.

This is known as a carry trade in Tradefi. When there are huge fluctuations in the carry trade, the yield in Tradefi decreases, leading to a drop in interest rates on mainstream lending platforms like AAVE and Compound. Additionally, there is a possibility of depegging for stablecoins in DeFi, as their application scenarios are still limited.

So, when liquidity tightens, users may increasingly price their lives in fiat currency, thus even if they borrow stablecoins like DAI, they will still exchange them for USDC or fiat currency in CEX. Therefore, we will find more traditional giants and whales starting to short stable coins to cause them to depeg, which presents an arbitrage opportunity.

Coincidentally, also due to factors such as the imperfect credit algorithm models of credit-related businesses, the over-collateralization model of DeFi has become mainstream, ensuring the security of lending platforms and the liquidity of the treasury to better control risks.

Over-collateralization is not perfect, and the risks that may arise include:

• The over-collateralization model is a leech in some liquidity-deficient public chains. When you borrow a large amount of ETH, BTC, USDC using the native protocol assets of that chain for liquidity, you are essentially draining the liquidity of the non-native assets of that chain. This results in certain public chains having a high TVL but mostly consists of native assets that are difficult to liquidate ( unless you are willing to endure extremely high slippage on the DEX ).
• The over-collateralized model has brought about the Debt Ceilings( debt ceiling issue).
• The asset prices in the crypto market may remain in a state of extreme volatility for a long time, as excessive collateral can easily lead to a highly panicked bank run. To ensure the safety of the liquidation line, whales are likely to sell Alt Coins to gather liquidity to fill the collateral.

However, relatively speaking, for the crypto market that is still in the extreme dark forest stage, over-collateralization is indeed a better way to control risks. For the native liquidity of crypto, the most suitable target should be the stablecoins issued through over-collateralization. A chain liquidation might be the best evolutionary way for Crypto, and whether the collateral can support this big banner is also very important.

Not long ago, AAVE announced the launch of its over-collateralized stablecoin (GHO), which is likely to capture some market share of stablecoins. We need to observe whether GHO can quickly establish some application scenarios in several DeFi protocols by leveraging AAVE's endorsement. Before this, I was still contemplating what an on-chain bank really looks like lol, and there might soon be an answer.

3. The Importance of Decentralized Identification and Reputation Systems

The flaws in the credit assessment system reflect the importance of the DeFi native certification system and decentralized reputation scoring system.

Here I choose to share ARCx. From the perspective of the slogan, it addresses my confusion about over-collateralization and privacy, including questions about the credit scoring system. However, we still need to observe its adoption rate. Additionally, we need to see whether the designed credit scoring system can truly solve the above issues in practice.

It has designed a DeFi Passport(0-999 score), ARCx will generate a credit score based on past interactions of users' wallets with various DeFi protocols. The evaluation criteria include many variables, such as loans, liquidations, airdrops, and user behavior, etc.

Andrew Beal mentioned in his recent post:

"The DeFi ecosystem is a new quadrant of the financial system, but from a reputational perspective, it is an island separate from the mainland. Why?

No identification.

All the work you've done to build a reputation in the traditional financial system doesn't apply, because the DeFi ecosystem doesn't know who you are. It's like transferring schools halfway through your junior year. Everything you've done in your first two years is gone, and you have to start over.

4. Build a Decentralization Identity System

By breaking down and data-constructing the term "身份", we allow users' identification and data to have uniqueness and combinability. We need a minimal "DID protocol".

When the term "identification" is placed in the network, we can seemingly decompose it into a combinatory framework of storing, managing, and retrieving information.

But "identification" involves the "philosophy of self(", when we discuss "self", we should consider that a person is a whole existence. Identification is a person's social attribute, and to some extent, it is also a person's value.