> For the complete documentation index, see [llms.txt](https://lucia-protocol.gitbook.io/lucia-protocol/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://lucia-protocol.gitbook.io/lucia-protocol/attribution-credit-scoring-system.md).

# Attribution Credit Scoring System

Lucia Protocol introduces an innovative Attribution Credit Scoring System, engineered to deliver an accurate and comprehensive assessment of borrowers' creditworthiness. Unlike traditional models that heavily rely on a singular data set, Lucia's system adopts a multi-dimensional approach by amalgamating both on-chain and off-chain data.

The On-chain Score is computed by aggregating key parameters such as users' transaction history and interactions within the blockchain network. This rich layer of data offers a granular view into users' financial activities and risk profiles, thereby augmenting the reliability of the credit evaluation.

**On-Chain Score Formula:**

<figure><img src="/files/s37ZEN8bPK14Jn40WuVh" alt=""><figcaption></figcaption></figure>

In addition to on-chain data, Lucia's credit scoring mechanism incorporates off-chain sources, delving into external financial data such as credit history and employment records. By considering a broader range of financial activities and behaviors, the mechanism forms a complete picture of borrowers' financial standing.

**Off-Chain Score Formula:**

<figure><img src="/files/zCyspNbpouDZWi4QvG1n" alt=""><figcaption></figcaption></figure>

**Combined Credit Score Formula:**

<figure><img src="/files/BydwV4arRer5QOs9hzfH" alt=""><figcaption><p>Where w1 and w2 are weights assigned to on-chain and off-chain scores, respectively. </p></figcaption></figure>

The integration of on-chain and off-chain data results in a comprehensive overview that minimizes reliance on a single data source. Consequently, Lucia's Attribution Credit Scoring System ascertains creditworthiness with a higher degree of accuracy.


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