The answers to all your questions, at least the main ones!

If you don't seen an answer you're looking for, please ask in the Cred Community Discord Server. The Cred Protocol team and community members are ready to jump in an help.

How does it work?

Cred Protocol uses on-chain analytics to quantify lending risk at scale. We correlate transaction history with the account owners ability to fulfil obligations, specifically, repay loans.

Our machine learning credit score model is comprised of a set of features that have been selected to capture the holistic view of an account's on-chain risk. When combined, they create a predictive score that quantifies the creditworthiness of an account.

As the web3 ecosystem continues to grow and mature, we are always looking to add features that inform the model and improve the score. This process of continuous development is driven by our search for new data sources as they emerge, including new lending protocols, chains, and broader web3 projects.

What factors affect my score?

Revealing the individual features that contribute to the score would potentially lead to people being able to 'game' the score, and improve their score without improving their underlying fundamental behaviours. In order to preserve the score's integrity but also provide transparency, the features are grouped into high-level 'Credit Factors'.

A table of the Credit Factors, alongside a more detailed breakdown of each factor is listed below:

Credit FactorsDescriptionImpact

Borrowing History

Features linked to historical loan repayment performance.


Account Composition

Features linked to the asset breakdown within an account.


Account Health

Features linked to the size and volume of activity within an account.



Features linked to the account's involvement in the web3 ecosystem.



Features linked to trust and transparency.


New Credit

Features linked to recent and open credit history.


To find out more about the credit factors, read here

How do I improve my score?

The easiest way to improve your score is to use lending protocols, take out loans and then repay them successfully, this demonstrates strong creditworthiness that will be reflected in a higher credit score.

However there are ways to improve your credit score beyond interacting with lending protocols. The Credit Factors represent groups of features that contribute to the score, improving behaviour in any of these areas would have a positive impact on your score.

Why is my account unscorable?

We are able to score any account with on-chain Ethereum mainnet transactions, if your account does not have any Ethereum mainnet transactions then it will not be given a score. Once your account has transactions it will be possible to score it.

Similarly, rather than giving a brand new account with no transactions a score of 0, we will return 'Unscorable' as there are insufficient transactions to generate a score.

What if I have multiple wallets?

We are able to provide a score to a single account on the basis of its transaction history. Similarly if you have a number of accounts, we are able to amalgamate their combined transaction history to produce a single score for the entire group.

How do you stop someone 'gaming' the score?

Our score is designed so that creditworthiness is informed by legitimate account activity. We have layers of on-chain analysis, fraud mitigation techniques and a suite of Accountability APIs that surface consequence for bad actors. We don't publish exact details of our scoring algorithm to mitigate manipulation.

How do you mitigate someone boosting their credit score by transacting with their own accounts?

Using on-chain analytics, we’re able to track transactions which pass between different accounts and back to the same account helping to mitigate “self dealing” which may inflate transaction volumes and aspects of the score. Other aspects of the score are focused on Trust and evaluate multiple “proofs of humanity” ranging from verified credentials to fully KYC’d identities which make it more difficult for an account to be abandoned or transferred.

How do you prevent someone building up a good credit score, taking out a loan and then intentionally defaulting?

The short answer, is: where appropriate we verify identity. We use proprietary on-chain analytics to mitigate fraud and partner with leading identity verification and attestation protocols to support the credit decisioning process. In addition, we’re actively exploring privacy-preserving identity attestation approaches which combine security and pseudonymity. Learn more.

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