zkCredit Score
zkCredit Score enables private, trustless verification of real-world credit scores with zkTLS and ZKPs, giving users self-sovereign financial reputation without exposing identity or financial details.
Last updated
zkCredit Score enables private, trustless verification of real-world credit scores with zkTLS and ZKPs, giving users self-sovereign financial reputation without exposing identity or financial details.
Last updated
Privacy first: Leverage zero-knowledge proofs and zkTLS to verify credit scores without exposing sensitive financial or identity information.
User-centric reputation: Validate creditworthiness using reliable, off-chain credit score data from established providers.
User-centric reputation: Built to give users ownership of their financial reputation, enabling trust in decentralized ecosystems.
Fully reusable: Once verified, users can reuse their zkCredit Score credential across ecosystems without repeating the verification process.
Decentralized & Secure: Sensitive credit data remains off-chain—only cryptographic proofs are shared, preserving privacy and minimizing risk.
Plug-and-play: Easily integrate zkCredit Score into your platform using our SDKs to enable secure, privacy-preserving credit verification in minutes.
The zkCredit Score procedure enables privacy-preserving verification of a user's real-world credit score without revealing sensitive financial or identity data. It leverages trusted credit data sources and zkTLS to validate score authenticity while preventing fraud or manipulation. Here's a high-level overview of the procedure:
Credit Score Verification Flow:
Generate QR Code: The zkMe widget generates a unique QR code for income verification.
Scan via Mobile Device: Users scan the QR code using their mobile devices.
Redirect to Portal: Upon scanning, users are automatically redirected to the zkTLS interface via an Instant App, App Clip, or Native App.
Login: Users follow on-screen instructions to log in via the designated method provided by the trusted credit data provider.
Authorize Data Sharing: After logging in, users will see a "Share Data" button. By clicking it, they authorize the system to proceed.
Automated Data Retrieval: The system automatically extracts key credit score required for following ZKP generation. No raw data is exposed during the process.
Score Rating & Classification: After retrieving the credit data, the system classifies the user's credit score based on FICO score tiers. This classification result is then used to generate a ZKP, representing the user's score rating in a privacy-preserving format.
Generate Random Numbers: The user's device generates a random number as part of the zkCredit Score process.
Zero-Knowledge Proof (ZKP) protocol:
Commitment Phase: The user generates a cryptographic commitment. This commitment includes hashed information about income without revealing actual coordinates or sensitive data. And the commitment is securely stored on the user's device, ensuring it cannot be tampered with.
Challenge Phase: The verifier (the service or entity performing the verification) selects a random challenge to ensure the user's commitment is valid and sent to the user's device for processing.
Response Generation: The user’s device processes the challenge by combining it with the previously generated random number and the commitment, then sends the response back to the verifier.
Verification: The verifier checks the validity of the response and whether it satisfies the accredited investor criteria, without gaining knowledge of the user's actual coordinates.
Verification Result: Based on the verification outcome, the verifier can assess whether the user’s score falls within the required ranges, without revealing the actual credit score or exposing any sensitive personal data.
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