Today we are excited to share that we are coming out of closed-BETA and are now open to the public. In practice this means that if you are a web2 or web3 business that needs access to risk data and credit scoring, we would love to hear from you and we are ready to help
Cred Protocol’s on a mission to bring trust and transparency to web3 by quantifying lending risk at scale. For the last 12 months we have been analyzing on-chain and off-chain data to evaluate an account owner’s ability and willingness to fulfill obligations, specifically to repay loans.
In partnership with our early customers we have been developing a suite of credit services to enable them to embed risk decisioning and an understanding of creditworthiness into the heart of their businesses.
Our products leverage enterprise grade data ingestion pipelines, we train machine learning models on data generated across chains and protocols to produce a suite of services that are available via web API and Chainlink-based credit oracles.
- Credit Scoring
Cred Protocol’s credit score (in the range 300–1000) covers over 200m accounts and is informed by on-chain transaction activity associated with a single account address, or collection of accounts addresses (”identity-based scoring”).
Examples of account activity include (but aren’t limited to): account age, transaction frequency, total asset value, total debt value, percentile of asset value relative and percentile of debt value relative to the population of accounts, asset composition (ie. stablecoins vs. altcoins).
Transaction history is correlated to the account owner’s ability to fulfill obligations, specifically, repay loans. Cred Protocol predicts the likelihood of borrowers being liquidated or defaulting on loans in the next 90 days. This probability is evaluated across the population of accounts to produce a “score” that measures relative creditworthiness.
2. Credit Reporting
Cred Protocol’s credit reporting services provide the raw data and aggregated statistics that power Cred Protocol’s credit score. Data attributes may also be used independently to inform custom credit models and credit decisioning processes. Sections of the report include:
- Account Summary Stats: Statistics on the current cross-chain balance, token composition, token value, NFT ownership, transactional volume, transactional count, and asset volatility within a wallet.
- Account Percentiles: For all of the summary statistics above, showing how the account ranks compared to other active accounts.
- Borrowing History Stats: Statistics covering the historical borrowing performance of the account including length of lending history, count and value of prior borrows, deposits, collateral value, repayments and liquidations.
- Borrowing Percentiles: For all of the borrowing statistics above, showing how the wallet ranks compared to other active accounts.
- Protocol Summary Stats: Breakdown of borrowing history by lending protocol, with stats on an account’s borrows, deposits, collateral, repays and liquidations. Also includes stats on the distribution of tokens on each protocol.
3. Credit Monitoring
Cred Protocol’s credit monitoring services provide the raw data and notifications to build a comprehensive on-chain monitoring solution. Once a wallet has been initially scored, monitoring allows for the analysis of subsequent behavior. Monitoring functionality includes:
- Event Monitoring: For a given protocol, the monitoring of adverse events such as: late payment, delinquency, default, liquidation. This can also be done as proactive monitoring, where Cred is able to identify the wallets that are at-risk or approaching an adverse event.
- Score Monitoring: For a wallet (or group / cohort of wallets) Cred is able to monitor their credit score changing over time, this could either be event driven score changes (such as a score change following an adverse event) or time driven score changes. This enables a dynamic understanding of how an account’s risk profile changes over time due to its subsequent behavior.
4. Credit Rating
Cred Protocol leverages its data ingestion platform to inform credit rating services (range of A-D) based on on-chain and off-chain data sources. Our Rating process examines factors such as (but not limited to): financial performance, balance sheet strength, real-time on & off-chain data, operational robustness, and management maturity and strategy. Our Credit Rating services cover:
- Exchanges: analysis of exchange financial performance, liquidity and user metrics, currency pairs and price volatility.
- Protocols: analysis of lending protocol strength, originations and utilization, loans and deposits, liquidations and reserves, audits and smart contract security.
- Borrowers: rating of institutional web3 borrowers, leveraging traditional trad-fi fundamental credit analysis, supplemented with incorporation of on-chain assets and liabilities.
- Fintechs: rating of web2 or web2/3 crossover businesses, using traditional financials (PnL & Balance Sheet) alongside real-time information gathered via Open Banking & Open Accounting APIs.
The use cases
Whilst in closed-BETA we have been working with a collection of amazing partners to validate use-cases across the DeFi, web3, and traditional financing landscape. Whilst we believe these use-cases will multiply over time we wanted to share some examples of how Cred’s products are already being used.
Lending Protocols qualifying access & making decisions
We have been supporting the lending protocol Teller to embed on-chain risk analysis throughout their underwriting process, from qualifying initial loan applications, determining loan terms based on risk metrics, and monitoring repayment performance. This is a huge breakthrough for DeFi lending, and a step in the right direction towards capital efficient and ultimately under-collateralised lending based on the creditworthiness of individual borrowers.
Identity Protocols attesting creditworthiness
In traditional finance, identity and creditworthiness and intrinsically linked, and identity is the thing that incentivizes behavior and creates consequence. In web3 users are pseudonymous by default, and it has been amazing to work with protocols who are tackling the subject of identity. Working with Quadrata, Masa, Krebit, Convospace has demonstrated the versatility of Cred Protocol in supporting a variety of approaches to identity in web3 from Soul Bound Tokens to Verifiable Credentials. At the heart of all of the solutions is the belief that creditworthiness is a key part of users ability to attest and demonstrate their on-chain activity
Calanthia Mai, Co-Founder at Masa said that the Cred Score “changes the game and lays the foundation for true risk-based underwriting in DeFi lending. It is a revolutionary way to open up access to capital based on a self-sovereign, portable, and on-chain identity
A number of wallet providers have spoken to us about their desire to bring the credit scoring experience to their users, enabling their users to see their credit score alongside their holdings in order to educate them about responsible on-chain behavior and the impact that liquidations and defaults can have on web3 reputation. We are excited to continue to work with Metamask, ImToken and Valora on how to bring further insight and utility to their users .
Lending Pools rating corporate borrowers
We have partnered with Atlendis to provide a Credit Rating for a web2 fintech looking to borrow on the blockchain. Leveraging our ability to ingest data both on & off-chain we were able to provide a Credit Rating and Credit Report.
Talking about the partnership Marcos Miranda, Product Lead at Atlendis Labs said:
“Atlendis Labs chose to work with Cred because of their experience in assessing creditworthiness and the professional background of their team in this field. Given our focus on alternative finance, Cred was a good candidate to help establish the creditworthiness of fintechs in this area.”
Traditional Credit Bureaus & Fintechs exploring web3
Traditional Credit Bureaus and Fintechs are increasingly aware that digital asset activity is growing and that as a result, focussing only on bank data will result in less powerful risk scoring and missed lending opportunities. We are partnering with traditional financial institutions to demonstrate to them the power of digital asset data in opening access to credit and creating transparency over all aspects of financial activity.
Chains & Protocols we support
Central to the strength of Cred Protocol is the depth and breadth of the data that informs our products. Sourcing data from a wide variety of places is part of our quest to ensure that wherever digital asset activity is taking place, it is being reflected in our score.
Our products are informed by non-lending data from the following blockchains:
We ingest data from the lending protocols below, across multiple versions and chains.
- Aave: Versions 2 & 3 on Ethereum, Avalanche, Arbitrum, Avalanche, Optimism, Fantom, Polygon
- Compound: Version 2 on Ethereum
- Teller: Version 2 on Polygon, Ethereum
- Maker DAO: Version 1 on Ethereum
- Vesta: Version 1 on Arbitrum
- Banker Joe: Version 1 on Avalanche
- BenQi: Version 1 on Avalanche
- D-Force: Version 1 on Ethereum, Avalanche, Binance, Optimism, Polygon
- Geist: Version 1 on Fantom
- Iron Bank: Version 1 on Ethereum, Avalanche, Fantom
- Liquity: Version 1 on Ethereum
- Radiant: Version 1 on Arbitrum
- Uwu: Version 1 on Ethereum
- Venus: Version 1 on Binance
- Morpho: Version 1 on Ethereum
How to build
Launching Cred Protocol into Public BETA is the next step in our journey, and we are keen to help as many businesses as possible embed risk into their products and user experiences.
If this article has inspired you to build using the Cred Protocol, then you can create an account on our Developer Portal here. If you have any questions for the team please reach out to any of the team across our social media channels and we would love to help.
If you want to hear from us on a specific topic please tweet us @cred_protocol.