Enabling Collateral in DeFi Lending — Why Your Favorite Token Might Not be Listed Yet

Authors: Lavi & Dabar90

TL;DR

• In this article we analyse the collateral listing process of Aave, Compound, Euler Finance and MakerDAO
• While the basic flow of the process is quite similar, each protocol has distinct elements — especially when it comes to risk assessments — that are used to determine the final decision
• Most of the older protocols have a very thorough and resource-intensive listing process; only Euler uses a unique and permissionless approach
• After an asset is listed, only market-related risks are continuously monitored, which leads us to the conclusion that there is high potential for Service DAO’s to support streamlining the listing process, as well as the continuous monitoring of other risks

Introduction

Adding a new collateral to a DeFi protocol can be a cumbersome process that differs quite significantly between protocols. There are many considerations that flow into the final decision before adding a new token. Most of them are risk-related, such as technical risk, market risk, centralization risk or legal risks. Other considerations look at the potential the asset can bring once listed, such as potential for TVL or additional loans.

In this article, we are going to look at different approaches applied by the most prominent lending protocols in DeFi. In the first step, we will analyse each approach and then compare them in order to determine what the differences are and how we can use different strategies for risk and quality assessments.

Adding Collateral

Leading money market protocol Aave has 32 assets that can be deposited into the protocol as collateral. Close competitor Compound on the other hand has only 17 assets available for deposit, while new entrant Euler already has 64 assets enabled. However, in terms of collateral, Euler is actually more conservative than its older peers, as of today only seven of all available tokens are actually enabled as collateral.

The difference between the OGs and the new kid on the block, is the effort required to list an asset on one of the protocols. Euler is designed to be a permissionless lending protocol, whereby any asset can be listed (in the lowest tier) without the need of governance, which makes it an ideal candidate for long tail assets. Aave and Compound on the other hand have more stringent processes to add new collateral, which are permissioned through their governance systems. The same is true for MakerDAO, the issuer of the stablecoin Dai has core teams that evaluate each new asset applying for collateral status, however, the final decision is always left to token holders.

In the next sections we will look at all four protocols and compare their processes for listing a new asset to their respective protocol.

Getting listed on Aave

On Aave, assets can be listed in many different markets, whereby each market operates as a segregated risk pool, and every newly added asset affects the risk of that particular market. For instance, Aave has different versions of markets that are still live (V2 & V3), there are markets for distinct chains (e.g. Ethereum mainnet, Arbitrum, Polygon, etc.) and there is also an AMM market, to which users can deposit LP tokens as collateral.

For a new asset to be added to one of these markets, there is a five-step process whereby four main considerations must be covered by each proposal and discussion:

1. The increased insolvency risk of the market it is listed in
2. The potential to expose the market it is listed in to a single point of failure
3. The risks associated with collateral currencies
4. The benefits of protocol/market diversification

All of the above points are looked at in detail throughout the listing process, which consists of the following five steps:

Step 1 — Create an ARC: Proposing the asset via an Aave Request for Comment (ARC):

• An ARC for a new asset can be initiated by using a template, to provide information about the protocol (e.g. link to whitepaper, source code, Ethereum addresses contracts, ChainLink Oracle, etc.). The template also requires details about the token and a rationale for why listing the asset should be beneficial for the Aave ecosystem
• In addition to the ARC, a Risk Analysis is required to understand the underlying risks and to define the parameters for integration. The risk assessment covers smart contract risks, counterparty risks (decentralisation) and market risks.

Aave risk framework and risk factors (source: Aave Risk Framework)

• Next, the Parameter Suggestions are added, whereby the proposer shares the risk parameters and interest rate curves that are considered in case the asset is listed. In contrast to other risks listed above, risk parameters are monitored further once the collateral is listed. Typically three risk parameters are applied, these are liquidation bonus (liquidation incentive), loan-to-value (collateral factor), and liquidation threshold (close factor). For Aave and Compound, these parameters are monitored by Gauntlet and dynamically adjusted depending on market situation.
• Finally, a Snapshot vote is set up (requires 50 $AAVE) to gather Community Sentiment. This step helps in checking community interest and risk parameter preferences.

Step 2 — Preliminary AIP: After positive community sentiment, an AIP can be prepared using the same template as in the first step. However, proposing an AIP currently requires a threshold of 80k $AAVE the proposer needs to hold or have delegated.

Step 3 — Chainlink price feed: Every asset requires a price feed that needs to be requested by contacting Chainlink or Aave Genesis team.

Step 4 — Prepare the Payloads: Each asset listing proposal must include the necessary payloads (e.g. aToken, debtTokens, and InterestStrategy contracts). Here is where the on-chain preparation begins, along with a pull request for token parameters and a deployment script.

Step 5 — Submission of proposal: The proposal can now be submitted on-chain, including all of the information from the above steps.

In summary, the Aave listing process tackles many relevant risks that come with a new asset. However, some are looked at in more detail and others are considered on a higher level. As displayed above, the smart contract risk and centralization risk are evaluated using only two proxy metrics, i.e. maturity (days of existence of the smart contract) and number of transactions. The older and the more transactions, the less risky. To estimate the centralization risk, the framework looks at the number of token holders and the centralization of permissions.

It can be argued that once a standard framework is provided, its benchmarks can be increased artificially to achieve the required threshold (e.g. in this case, the number of token holders or trading volume). However, this would need to be done over a prolonged time period, for the listing process can take months and it can be assumed that Gauntlet would point out potential issues when doing their assessment. Nonetheless, as we’ll learn later on, other protocols look at more metrics to estimate specific risks.

Getting listed on Compound

Compound’s listing process was recently reviewed by OpenZeppelin and supplemented with checklists and guidelines. The Compound asset listing process consists of the following 9 steps:

Step 1 — Initialization: Starting the procedure by filling out a checklist to provide context about the asset and associated risks. The initial checklist is the most comprehensive protocol overview — that is mostly a preliminary risk assessment — out of all four protocols. The template covers the following sections, whereby the smart contract category requires the most information. The list below is an overview and not exhaustive:

• General — a protocol overview and links to resources
• Market risks — historical volatility, liquidity on exchanges, emissions schedule, etc.
• Decentralisation — token distribution, privileged roles, is it pausable, blacklist, etc.
• Smart contract risk — codebase & on-chain activity, security, smart contract behaviour, upgradeability
• Initial requirements — setting the initial risk parameters

Overall the full checklist consists of 56 individual questions and check marks that need to be answered. This task is currently done partially by community members, OpenZeppelin and Gauntlet.

Step 2 — Community check: The proposal is first posted on the forum and the community reviews the information provided in the checklist

Step 3 — Risk analysis: In this step, Gauntlet conducts a risk assessment as outlined in their framework. Within this asset, Gauntlet looks at specific risks related to:

• Security aspects of the proposal and potential governance impacts for Compound
• Market risks, such as price manipulation, insolvency and liquidity risk, not incentivized liquidations and cascade effects
• Asset specific risks, such as compatibility and compliance

Essentially, the results are used to determine a recommendation for an initial risk parameters setting (Reserve Factor, Collateral Factor and Borrow Cap). However, Gauntlet specifically declares that they do not cover oracle risk, infinite mint attacks, governance attacks, smart contract risk, centralization risk, or other technical risks and they defer to OpenZeppelin for these categories.

Step 4 — Tooling and simulations: The community checks if the implemented contract matches the base implementation with the expected parameters

Step 5 — Contracts deployment: Contract are deployed (potentially on testnet), which also serves as a check whether new oracles need to be set up

Step 6 — Formal proposal: The formal proposal is drafted

Step 7 — Audit: The proposal is audited by OpenZeppelin or another third party

Step 8 — Proposal submission: Proposal is submitted for voting on-chain (this requires minimum of 25k $COMP tokens) and voted on by COMP holders

Step 9 — Post-Launch Parameter Update: Parameters such as collateral factor or reserve factor are updated once the asset is live

By comparing both Aave’s and Compound’s listing process, it becomes clear that they both consider mostly the same risk categories and the process is similar. However, Compound does have more requirements in the initial phase (longer checklist) and they also audit the proposal before final submission, which is not the case at Aave.

On the other hand, Compound hasn’t added a new asset since February 2022 and only seven assets have been proposed for listing within the last 12 months. It can be assumed that the time consuming and strict listing process plays a role here.

Getting listed on Euler Finance

Euler has introduced a new concept for permissionless token listings, targeted toward long-tail assets. The difference between Euler and its older peers is that Euler has introduced a system of asset tiers, defining what each asset can be used for. This allows Euler to reduce the asset listing process to one requirement — at least for the lowest tier — which is a WETH trading pair on Uniswap V3. This pool serves as the oracle for the time-weighted average price (TWAP) to analyse TVL and slippage metrics for a TKN/WETH pair.

The Euler risk management concept uses the following asset tiers:

1. Isolation tier — available for lending and borrowing, but cannot be used as collateral for borrowing other assets. Assets in the isolation tier can only be borrowed in isolation from other markets because liquidation events cannot affect other markets
2. Cross Tier — available for lending and borrowing, cannot be used as collateral but can be borrowed alongside other assets. Cross-tier assets allow more flexibility in collateralization but also add more risk to the protocol than assets from the isolation tier. Hence a first risk assessment is required to enable a token for this tier.
3. Collateral tier assets are available for ordinary lending and borrowing, and cross-borrowing, and they can be used as collateral.

Step 1 — Permissionless listing: As mentioned above, adding an asset to Euler only requires a TKN/WETH pair on Uniswap V3.

Step 2 — Risk Rating: To assess whether an asset can move up to a higher tier, the team has implemented a rating system to evaluate the following four risks:

• Smart contract risk — a check whether the protocol was audited, the number of days the protocol has been functioning without hacks and deeper research if needed
• Centralization — this is measured by estimating the median size of token amount per holder. When the ownership structure isn’t transparent, they employ more forensic due diligence
• Volatility — this parameter is measured via realised volatility (and implied, if available)
• Liquidity — this is measured by estimating historical slippage caused by a certain amount of volume

Step 3 — Governance Vote: The risk ratings are used to define the risk parameters which are added to the proposal. Finally, it’s the EUL token holders deciding via governance vote whether an asset can move up to a higher tier or not.

In addition, Euler displays the oracle risk for each asset, which is based on the Uni V3 TWAP and measured by Cost-of Attack. An open-source oracle tool was developed to assess this.

Moreover, Euler also looks at the borrow factor. The metrics used to define the regular collateral factor are also considered for defining the borrowing factor, to evaluate the risks associated with the asset that is being borrowed. For Aave or Compound, borrowed assets are mostly stable coins. With Euler, however, more volatile assets can be borrowed which introduces additional risks. In that way, Euler takes into account risk for both sides — collateral and debt asset risks.

In summary, asset listings on Euler Finance are permissionless, but currently limited to Uniswap V3 WETH pairs (a Chainlink integration is also planned). Every asset starts at the isolation-tier level and EUL holders decide via Euler’s governance system if an asset can be moved to a higher tier. The proxy metrics used to assess the risk ratings are few in numbers and, similar to Aave’s risk assessment, a predefined framework of standards decides what rating is given.

Getting listed on MakerDAO

The collateral onboarding process for MakerDAO is slightly different from the three lending protocols described above, because in this case, it is a CDP (Collateral Debt Position) protocol that functions as a stablecoin issuer (DAI) and all processes over protocol are governed by community. Getting listed on Maker basically implies that the token can be used as collateral, which is not necessarily the case for a listing on a lending market.

At Maker the collateral onboarding process is more complex, detailed and targeted for community involvement, compared to the previous protocols. Another difference to the lending markets above is that MakerDAO — in addition to crypto-native collateral — allows onboarding collateral in the form of Real-World Assets (MIP67). However, for this article we only focus on collateral listings of ERC-20 tokens.

Step 1 — Application: For crypto-native collateral (ERC-20 tokens) the procedure starts with the Collateral Onboarding Application which is then published on the MakerDAO forum, where the application will be discussed over two weeks. The following points are covered within the application (not exhaustive):

• Background information — Overview, history, links to resources and info about the party requesting the listing
• Asset information — Type of asset, exchange listings, MCap, oracle data sources, etc.
• Business questions — Expected use case of the Dai generated by the vault, strategic benefits for MakerDAO
• Legal questions — legal risks associated with the collateral, jurisdiction, regulatory registrations of the asset, decentralised vs trusted asset, etc.
• Technical questions — Audits, access control, whitelist/blacklist function, upgradability, rebase mechanism, etc.

The application form is similar to the checklist used by Compound, but instead of 56 items this first check only requires 36 inputs. Further, the list is less heavy on technical risks, but therefore has more questions related to the legal situation of the asset.

Step 2 — Greenlight Poll: After the two week discussion period, the proposal is eligible for Community Greenlight Poll, an on-chain poll that measures community sentiment about the proposed collateral type. These polls usually last 2 weeks and are scheduled for the first or third Monday of the month.

Step 3 — Collateral Status Index: All proposed collateral types that pass through the community greenlight polls are added to the Collateral Status Index spreadsheet and Collateral Onboarding Prioritization Framework spreadsheet by a Governance Facilitator or the collateral onboarding domain teams.

MakerDAO has three domain teams for collateral onboarding assessment. Each is responsible for covering distinct aspects of the listing evaluation:

• Collateral Risk Evaluation (by Real World Finance Core Unit) — covering background, market risks via token metrics or exchange activity, DeFi presence, and risk parameters (see example)
• Oracle Assessment (by the Oracle Core Unit) — covering components such as Median and OSM (see example)
• Smart Contracts Technical Assessment (by the Protocol Engineering Core Unit) — covering technical risks related to the smart contracts and the token (see example)

Step 4 — Governance Poll: After each domain team conducts a collateral assessment for its area, it publishes an assessment on the Maker Forum and begins the Governance Poll, which measures the sentiment of MKR holders with regard to the published assessments.

If the Governance Poll passes, it is necessary to schedule an Executive Vote within 30 days. This time period allows the domain teams to further test and verify the collateral type for onboarding. If the Governance Poll doesn’t pass, the collateral may be resubmitted up to two more times.

Step 5 — Executive Vote: The Executive Vote proposal is written by a Governance Facilitator, and the Executive Spell is prepared by the Smart Contracts Domain Team. If the Executive Vote passes, the collateral asset will be added to the Maker protocol by activating the Executive Spell.

In summary, the Maker DAO collateral onboarding process requires three governance events (two polls and a voting event). In comparison, that’s at least one more vote than the other protocols we looked at. Furthermore, MakerDAO’s assessment goes into more detail on most risk categories compared to the other protocols, except for the smart contract risk, where Compound’s evaluation is more comprehensive.

A Comparison of all Processes

In conclusion, all of the four processes follow a somewhat similar approach. However, the differences — especially in determining the risks related to the collateral — are quite significant and MakerDAO as well as Compound are leading the evaluation process when measured in depth of the risk assessment. However, the advantages of fast-tracking the listing process are obvious, shown evidently by the difference in assets listed on each protocol.

The image below displays all stages of the processes and their differences, leading to the final decision, which is always left to the respective token holders via a governance vote.

Similarities

In summary, the following similarities stand out:

• Overall, the processes are subdivided into similar steps, starting with a template for the initial proposal and a community sentiment check, and ending with a governance vote
• When it comes to the risk assessment, the same categories are evaluated by all protocols. These are market risk, counterparty risk (decentralisation) and technical or smart contract risks. There are, however, significant differences in how risks are measured, but more on that later
• In general, there are high upfront costs for investigation and research before it comes to a first signalling vote (expect for Euler)
• All protocols use on-chain voting systems for the final vote (also Euler is about to launch governance
• All protocols will adjust an asset’s “status” in a later phase. This means that after a new asset gets listed, its collateral factor and other risk parameters are either decided after the listing occurs (at Compound the initial collateral factor is 0), or they can be changed later on, thus affecting the assets status. These risk parameters are decisive for whether the asset can actually be used as collateral and how efficiently it can be used. For Compound and Aave, it’s Gauntlet’s dynamic risk parameter proposals that do this. For Maker it’s the risk teams that propose the changes, and for Euler it’s the tier system through which an asset can be promoted to a higher tier

Differences

As we alluded to before, all of the protocols also differ quite significantly in certain areas of the process. Let’s dive into some of the most prominent distinctions:

• Only Aave and Compound employ third party service providers to support risk assessments and audits (i.e. Gauntlet and OpenZeppelin)
• MakerDAO has the whole process internalised, so that the community and specialised core groups of the DAO cover all of the work
• Compound is the only protocol conducting an audit of the final proposal before submission
• There are also differences in oracles being used, which influences the onboarding process. Euler uses the TWAP from Uniswap V3, Aave and Compound use Chainlink’s price feed — in addition to a backup oracle (e.g. Uni V2 for Compound) — and finally Maker uses its own oracle module that is deployed for each collateral type.

Further, there are multiple differences when it comes to risk metrics and the measurements that are applied:

• Euler has the lightest assessment with only five proxy metrics used to evaluate the associated risks. They heavily rely on their oracle price manipulation tool and that the users of the protocol take it into consideration when deploying or borrowing funds
• Compound has the longest checklist for risks, with a strong emphasis on technical and smart contract risks
• Aave and Euler provide and apply a public risk framework, resulting in a rating for each risk metric
• Market risks are always used as a basis to derive risk parameters (e.g. collateral factor), but there is no standard. All protocols look at similar risks, but use different proxy metrics to measure them. Some examples are:
• Aave looks at market cap, average 24h trading volume and normalised volatility (measured as normalised fluctuations in the price and calculated as the standard deviation of the logarithmic returns)
• Compound uses market cap, volatility (measured as standard deviation of log-returns for specific time frame), liquidity on largest exchanges, and the total supply plus the tokens emission schedule
• Euler evaluates liquidity (measured by historical slippage), and volatility (measured as realised/implied volatility)
• MakerDAO looks at many different aspects to determine risk parameters, which also seem to be different depending on the asset. However, market-related risks are measured by available liquidity (measuring slippage), trading volume on DEXs and CEXs, downside risk (in correlation to ETH) and other integrations within DeFi (see example here and here)

Final Thoughts

Collateral listings are a lengthy and comprehensive process, and typically the duration from start to finish takes several months for the more conservative protocols like Compound and Maker. To conduct this procedure, only Compound and Aave employ third party service providers, both of which are centralised entities.

We also noticed that only market-related metrics are actually continuously monitored, mostly to inform risk parameter adjustments, while the larger rest of the risk assessment is basically a one-time task. The exception here seems to be MakerDAO, where the risk teams also take into consideration other changes affecting an asset. It can be argued that only market related risks have a high possibility of changing for the worse very quickly, while other risks such as smart contracts or centralization change much slower. However, this nonetheless poses the question: Why do all this research, when the large majority of the risk metrics used to conduct the initial assessment are not monitored after the listing?

In conclusion, we truly believe that there is high potential for streamlining parts of the process, for instance by leveraging external service providers that are able to conduct the required research in a more scalable approach and in addition, can offer a monitoring service to ensure that also decentralisation, smart contract and other relevant risks are kept under surveillance. Especially for newer and less wealthy protocols that can’t afford the expensive services of Gauntlet or hire their own risk core-unit, risk-evaluation-as-a-service could be an interesting option.

At Prime Rating we have developed a comprehensive framework to evaluate quality and risks in DeFi. Together with DeFi Safety, our solution covers everything from smart contract risk, to decentralisation and tokenomics, team experience, as well as governance influence and thus potential threats through permissions and access keys. Moreover, through our community-based and open source evaluation process, we ensure up-to-date reports that can easily be turned into a monitoring service.

To sum it up, we have looked at the most established and prominent lending and stablecoin protocols within DeFi, plus one new entrant, and concluded that especially the former three apply very thorough risk assessments when it comes to allowing new tokens to be added to their platform. However the effort is less exhaustive when it comes to continuously monitoring the risks assessed.

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