At-Risk Borrower Credit Scores - User Level Risk Management

AUTHOR
Chris Brookins, Co-founder of RociFi

ABSTRACT
The credit score analysis is meant to build atop of Defishy existing analytics regarding borrowers ‘at-risk’ of liquidation. This analysis drills into a borrower’s riskiness based on their credit score, i.e. likelihood of default (or liquidation in case of Euler).

User level risk analysis is complimentary to protocol level risk management as borrowers with strong credit scores are risk-minded, thus unlikely to let their loans be liquidated, even with unexpected market volatility.

MOTIVATION
By understanding liquidation risk from a user level (micro) and protocol level (macro), Euler can best assess true insolvency risk to the protocol.

Our post is meant to offer sample scoring and risk metrics to the Euler community of a few at-risk positions, currently.

We also provide an expanded version of our analytics via spreadsheet of a subset of all Euler users for further investigation by the community.

If the community finds value in the information provided, we can provide weekly updates to either at-risk positions or spreadsheet.

AT-RISK ANALYSIS

Borrower 0xef764BAC8a438E7E498c2E5fcCf0f174c3E3F8dB
Per RociFi’s credit risk model, this address is rated a 3 out of 10, i.e. a strong credit score.

Historical activity across all of DeFi – not just Euler – include:

  • 274 total borrows, all-time
  • Wallet age of 1805 days
  • $201M in total debt repaid, all-time
  • Zero liquidations, all-time
  • $14.7M debt outstanding to Euler

The borrower has a strong credit score but current health factor of 1.01 is cause for concern. Despite the strong credit score, this position should be closely monitored until health factor increases.

Borrower 0x324E0b53CefA84CF970833939249880f814557c6
This address is rated a 3 out of 10, i.e. a strong credit score.

  • 6 total borrows, all-time
  • Wallet age of 1995 days
  • $359K in total debt repaid, all-time
  • Zero liquidations, all-time
  • $3.1M debt outstanding to Euler

The borrower has a strong credit score but current health factor is 1.01. However, the collateral and borrow asset are both USDC, which diminishes risk.

Borrower 0xC814Db50d7543D0f4aA8d8e5ceDCF4A40f8DC7F9
This address is rated a 4 out of 10, i.e. a good credit score.

  • 15 total borrows, all-time
  • Wallet age of 482 days
  • $2.5M in total debt repaid, all-time
  • Zero liquidations, all-time
  • $1.1M debt outstanding to Euler

The borrower’s good credit score, current health factor of 1.16, and collateral asset of USDC suggest low risk to the protocol.

Borrower 0x28a55C4b4f9615FDE3CDAdDf6cc01FcF2E38A6b0
This address is rated a 4 out of 10, i.e. a good credit score.

  • 4 total borrows, all-time
  • Wallet age of 482 days
  • $58.7M in total debt repaid, all-time
  • 3 liquidations, all-time
  • $300 total liquidated, all-time
  • $6.3M debt outstanding to Euler

The borrower’s good credit score and health factor of 1.46 suggest less risk to the protocol.

Hey! Thanks for this detailed presentation! Just a quick question regarding:

If the community finds value in the information provided, we can provide weekly updates to either at-risk positions or spreadsheet.

It is valuable indeed. But is it a grant proposal? If so, what are the conditions?

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I don’t have time to jump into the raw data at the moment. Can you let us know what assets this wallet is supplying/borrowing?

If they are looping/recursive borrowing, a health factor of 1.01 is only one factor of the equation. What’s their time to liquidation? You mention a collateral asset in the second wallet example but not in examples 1 or 3.

For example, I have opened up recursive borrows at a low health factor but with a high TTL. I monitor interest rates to ensure my TTL is above my risk appetite, and in that case, the health factor alone is less of a concern.

Also, how is the “fraud score” calculated? What does that even mean in the context of over-collateralized lending?

If you’re offering to do this for free (I don’t see mention of a price or commercial engagement in the proposal), I don’t see why not. If you’re looking for a grant or to work for the DAO, please include a price and breakdown. I’m not so sure this is something that Euler needs to pay for at this time (I can expand on that if this isn’t free).

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Hi @Raslambek! No grant proposal at this time. Just want to provide value to the Euler community for the time being while introducing credit scores as a risk management tool.

We could look for a grant at a later stage but that would be determined by community’s desires and needs. Some areas of grant proposal could include:

  1. Real-time dashboard of scores for all borrowers

  2. Collateral factor recommendations per user level and pool asset risk based on revenue / loss simulations

  3. Integrate credit scoring into the protocol as to offer higher LTVs to the best borrowers (increased capital efficiency)

We’ll let the community drive any of the above directions and subsequent grant proposals.

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Hey @defioperator.eth!

The assets supplied and borrowed are stETH which suggest recursive borrowing. Your comments are TTL are well noted and appreciated input to supplement the analytics.

Fraud score is the probability that a user is affiliated with ‘bad actors’ like hacks, phishing, exploits, etc. – a built upon a database of 1M+ known fraudulent wallet addresses. To be honest, fraud score isn’t relevant for Euler in regards to assessing liquidation risk, but could be useful for choosing rewards or customized LTVs for wallet addresses, if applicable, in the future.

Per my comment to @Raslambek, the weekly updates are free with no grant proposal attached.

Regardless, I’m still open to hearing objections to this offering if you feel it’s lacking in some regards given we’re trying to add value to Euler community.

For additional context on credit score benefits to lending protocols.

If you read the previous comments and thread, Gauntlet earmarked this borrower as posing a potential risk to Compound given its loan size and utilization. We commented that our scoring rated this borrower quite highly, thus they were unlikely to let their loan get liquidated. Furthermore, we identified 4 affiliate addresses that had a large amount of liquidity for them to utilize for ‘topping up’ their collateral, which is exactly what happened last week during the market volatility - bringing health factor back to 1.25.

Just one example as to how credit scores can be additive to risk management in bad markets, and additive to capital efficiency (revenue) in good markets.

Update:

Borrower 0xef764BAC8a438E7E498c2E5fcCf0f174c3E3F8dB
Per RociFi’s credit risk model, this address is rated a 3 out of 10, i.e. a strong credit score.

  • 300 total borrows, all-time
  • $201M in total debt repaid, all-time
  • Zero liquidations, all-time
  • $0 debt outstanding to Euler

**The borrower closed their position 6 hours ago. **

Borrower 0x324E0b53CefA84CF970833939249880f814557c6
This address is rated a 3 out of 10, i.e. a strong credit score.

  • 6 total borrows, all-time
  • $359K in total debt repaid, all-time
  • Zero liquidations, all-time
  • $3.1M debt outstanding to Euler

The borrower has a strong credit score with current health factor is 1.01. No change in status since last post.

Borrower 0xC814Db50d7543D0f4aA8d8e5ceDCF4A40f8DC7F9
This address is rated a 3 out of 10, i.e. a good credit score.

  • 15 total borrows, all-time
  • $2.5M in total debt repaid, all-time
  • Zero liquidations, all-time
  • $1.1M debt outstanding to Euler

The borrower’s good credit score, current health factor of 1.15 and collateral asset of USDC. No change in status since last post.

Borrower 0x28a55C4b4f9615FDE3CDAdDf6cc01FcF2E38A6b0
This address is rated a 4 out of 10, i.e. a good credit score.

  • 4 total borrows, all-time
  • $58.7M in total debt repaid, all-time
  • 3 liquidations, all-time
  • $300 total liquidated, all-time
  • $5.6M debt outstanding to Euler

The borrower’s good credit score and health factor of 1.46. Decreased debt sized by $700K since last update.

Hey! I’m not sure if this is the right place to share this information given that it does not pertain to a vote. Perhaps the #research channel in the Euler Labs discord? Thanks for the valuable contribution though - it’s awesome information you’re producing.

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