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  • 01 ReSource Finance
    • Glossary
    • Executive Summary
  • 02 Mutual Credit
    • 2.1 Definitions and Rationale
    • 2.2 History
    • 2.3 WIR Bank
    • 2.3.1 Modern Multilateral Barter Networks
    • 2.4 Mutual Credit on the Blockchain
    • 2.5 The Basic Economic Questions for DLT-based Mutual Credit Systems
  • 03 The ReSource Protocol
    • 3.1 Introduction
    • 3.2 Distributed debt collection and obligation enforcement
    • 3.3 Distributed risk management
    • 3.4 Underwriting and risk assumption
    • 3.5 The Underwriting process - a breakdown
    • 3.6 Ambassadors and network administration
  • 04 Monetary Flow, Reserves, Default Insurance
    • 4.1 Introduction
    • 4.2 Default Insurance
    • 4.3 RSD Savings Accounts
    • 4.4 RSD Autonomous stability and relation to the US Dollar
    • 4.4.1 RSD/USD Soft Peg
    • 4.4.2 RSD on the Open Market
    • 4.5 SOURCE Token Dynamics
    • 4.6 Monetary Buffering
  • 05 Protocol and Network Governance
    • 5.1 Introduction
    • 5.2 Reputation
    • 5.3 SOURCE Governance Token
    • 5.4 Initial SOURCE Allocation and Distribution
  • 06 Application Layer
    • 6.1 Introduction
    • 6.2 The Underwriting dApp
    • 6.3 The Ambassador dApp
    • 6.3 The Pool Aggregator
    • 6.4 The ReSource Marketplace
  • 07 TECHNOLOGY
    • 07 Overview
    • 7.1 Negative Balances & CIP36
    • 7.2 Non-custodial Key Management
    • 7.3 The Marketplace
    • 7.4 Distributed Underwriting and Data Aggregation
    • 7.5 Financial Data & Data Providers
    • 7.6 ReSource Credit Risk Analysis Algorithm
    • 7.7 “Pay with ReSource"
    • 7.8 Cross-network liquidity pools for interoperability
  • 08 Future Industrial Use Cases for the ReSource Protocol
    • 08 Overview
    • 8.1 Telecommunication
    • 8.2 Complex Supply Chain Financing
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  1. 07 TECHNOLOGY

7.6 ReSource Credit Risk Analysis Algorithm

Previous7.5 Financial Data & Data ProvidersNext7.7 “Pay with ReSource"

Last updated 3 years ago

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In partnership with , we've developed the first adaptation of an Underwriting Credit Risk Analysis (CRA) algorithm.

The main goal of the CRA is to give each underwriter a top down view of each member's health in the network and their stickiness. Traditional credit reports factor in exclusively credit and payment history. Since ReSource is a mutual credit network, we need to understand not only their traditional credit and payment history, but also their perceived value in the network. A member can have a sub par credit score, but if they are well perceived in their social circle/network, and the community values them, it should contribute a considerable amount to their protocol-native credit score as that score is only applicable inside of the network.

The CRA takes into consideration four key pillars. The score is an aggregation of both on and off chain data from each of the pillars below:

  • Financials

  • Social

  • Macro Industry

  • AML/KYC/Fraud

<Insert 3-axis graph from Teller>

The financial data is collected from both on and off chain data sources such as Dune Analytics, Plaid, Debank, Zapper, Twitter, Google, Equifax, prior ReSource Network history, and other similar sources.

Over time, as a user matures within the network their activity is monitored and added to their history. This allows underwriters to reassess and subsequently assign more credit. This, like a traditional credit score, can incentivize members to provide continuous value in exchange for more trust inside of the network.

The ReSource/Teller CRA is just one example of how a network can gather and analyze the data of each member in their respective network and provide guidance as to how much credit the underwriter can offer.

Teller Finance