Spectral

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MACRO Score

NFC (Non-Fungible Credit)

Decentralized Modeling

Programmable Creditworthiness

Spectral Lending

Lending Methodology

This lending methodology is a potential implementation of Spectral's MACRO score. If you're interested in collaborating on this product please reach out to us at [email protected]

Spectral's credit scoring system allows users to get loans with variable interest rates based on their credit scores. This is the first application of Spectral's NFC.
Our lending pool will consist of a 5 tick system of credit scores. The range of credit scores of each tick is determined according to actual credit score distribution data, so that the number of users in each tick is roughly the same. As an example, consider a skewed Gaussian distribution represented by the probability distribution function p(x), which is typical for the distribution of credit-scores in the real world:

A right-skewed Gaussian Distribution

The method of choosing ticks t_{i}:

$300=t_{0}<t_{1}<t_{2}<t_{3}<t_{4}<t_{5} = 850$

Is such that the following condition holds:

$\forall i\in \{0,1,2,3,4,5\}, \int_{t_{i}}^{t_{i+1}}p(x)dx = \frac{1}{5}$

As a lender, you supply to a single pool and the amount of "liquidity" per pool is decided based on an objective function around the utilization ratios per tick.

As a borrower you can only get money from the tick your credit score belongs to. The borrower's NFC acts as their identity card and mapped to a specific tick.

The interest rates are calculated based on the utilization ratio for that tick. The interest paid to lenders is simply the sum of the interest paid across ticks and split proportionally per lender. Borrowers pay interest referring to the tick they belong to.

Spectral Lending Pool Rebalance

In this scenario, composable credit worthiness allows users with higher credit scores to get access to lower borrowing rates than the market average via a unique liquidity rebalancing mechanism.

Our system constrains the utilization rate of each tick in each asset such as:

$U_{1} \geq U_{2} \geq U_{3} \geq U_{4} \geq U_{5}$

Where U_{1} is the utilization rate of the tick referring to the lowest credit score range and U_{5} is the utilization rate of the tick referring to the highest credit score range.

This provides an incentive for users to increase their credit score to access higher ticks and thus pay less upkeep for their open borrow positions.

The simplified architecture looks like this:

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