6.1 Credit loan scene

The credit loan model of encrypted assets is suitable for a wider range of loaning scenarios, such as project-specific fund loan, credit consuming loan, etc. The contract is based on the liquidity pool, relying on user portraits provided by trusted institutions, and perform decentralized credit evaluation, combining peer-to-peer matching and liquidity pool management for intelligent matching, to promote risk management and liquidity matching of credit loans.

Verification nodes and credit oracles

In order to obtain true credit information, DeCredit will establish a credit oracle service linking digital currency finance and the real world to serve credit loaning.

The first stage operates with the credit verification node mechanism and incorporates it into the oracle node to build two to three regional oracle networks. In the second stage, the oracle node will be extended to more third-party credit agencies, and a global collaborative oracle credit network will be built.

The core structure of DeCredit oracle:

• Oracle service

The Oracle service is to open up the individual credit profile and the basic services on the chain, and realize the mapping of the contract on the chain to the user profile.

• Aggre Smart Contract

A set of smart credit contracts running on the parachain, providing a credit service invocation interface, its function is to respond to user’s Oracle requests, reject and respond to applications according to rules.

• Credit Adapter

This is an off-chain data adapter running on the Oracle node, which receives aggregated smart contract instructions, routes to the designated collaborative oracle sub-center network (such as the US regional credit oracle, the EU credit oracle), and obtains the user's asset declaration credentials, asset status, and return the results to Smart Contract through the Oracle network.

Based on globalization, DeCredit's decentralized credit services include:

• Introduce credit data and solvency proofs accumulated in the traditional financial system, such as bank income flow, real estate proof or other proof information;

• Utilize the credit data of partners, such as by cooperating with mainstream exchanges, to provide users with a way to complete credit evaluation through exchange assets and capital flows;

• Relevant assets and transaction flow data accumulated over time in the system, such as loan flow.

Regional Oracle

Crediting is the basic work of the credit market, with obvious differences between countries and regions. Each country has its own complete operating mechanism and rule system. The United States, the European Union, and Japan use oracle services respectively.

For the oracle service of each sub-center, it is both unified and differentiated. Unity means that each sub-center oracle service interface uses the same Oracle service and the same smart contract set; difference means that each sub-center oracle only serves the credit information of users in the region, and their credit data and privacy protection are subject to local supervision.

The oracle service needs to rely on the credit data of authoritative institutions in various countries and regions. In order to promote the ecological development of the oracle service, DeCredit has dedicated 10% of the total amount of tokens to support the construction of the oracle service around the world.

Global Aggregated Credit Oracle

When two or three regional credit oracles are in mature operation, we will start to explore the construction of global aggregated credit oracles and upgrade the Credit-Scroing algorithm to make it suitable for globally aggregated credit products and oracle governance mechanisms.

Personal credit is a complex proposition. In order to provide credible credit evaluation, user data in multiple dimensions is required, and it needs to adapt to the regulatory policies of various countries. DeCredit will start from adopting a credit certification center and regional decentralization to a collaborative decentralization.

Credit-Scroing algorithm

The Credit-Scoring algorithm establishes different models based on the information entered by the user or the qualification information of the credit, through algorithms such as mathematical statistics, conducts a comprehensive analysis of the user's situation, calculates the individual scores of multiple dimensions, and finally gives the comprehensive personal score. User qualifications and models are carried out using smart contracts.