Cred.Hub
  • background
    • The Trust Deficit in Web3 Today
      • Enter Cred.Hub
    • Mission & Vision
  • introduction
    • Cred.Hub:Turning Trust into an On-Chain Asset
    • Reputation System
      • Reputation Scoring
      • Staking and Backing Mechanism
      • Reputation & Lending Market
    • Privacy, Integration, and Engagement Layers
      • Privacy Layer: Zero-Knowledge Proofs
      • Integration Layer: Cross-Chain Interoperability
      • Engagement Layer: Gamified Participation & Community Dynamics
  • Advantages of Cred.Hub
    • Cross-Ecosystem Compatibility
    • Economic Incentive Alignment
    • User-Friendly Onboarding
    • Cred.Hub Technology Architecture
      • Smart Contract Core
      • AI-Enhanced Scoring Engine
      • Zero-Knowledge Proofs (ZKPs)
  • Tokenomics
    • Tokenomics
      • Token Allocation
      • Utility
  • Roadmap
    • Roadmap
  • FAQ
    • FAQ
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  1. introduction
  2. Reputation System

Reputation Scoring

Cred.Hub aggregates three major data streams:

  • On-Chain Activity: Transaction histories, staking records, DAO votes, NFT engagements, lending and borrowing patterns.

  • Peer Ratings: Community endorsements, upvotes/downvotes, trust reviews, and role-based validations.

  • Off-Chain Verifications: KYC checks, social credentials (LinkedIn, GitHub), academic/professional certificates, and third-party attestations.

These streams are run through Cred.Hub’s AI-optimized scoring engine, which dynamically weights factors by context, applies time decay (so recent behavior matters most), and detects anomalies that could indicate manipulation.

Dimension

Example Data

Impact on Score

Financial Behavior

Repayment history, staking commitment

Affects creditworthiness, lending access

Social Trust Signals

Endorsements, reviews, DAO reputation

Impacts governance power, community role

Verified Credentials

KYC, verified affiliations

Opens access to sensitive or premium use cases

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Last updated 2 days ago