Credit scores for borrowing and lending money in the regular economy play an important role. Meaningful and critical financial decisions are underlined by credit channels such as Mortgages, Student Loans, Factoring, capital structures, and the list goes on. In web3 liquidity provides, lenders and others are constantly faced with the decision to whom or to which should they deploy their capital. So why not start this decision process based on a Credit Score?
What it does
S-Moody has developed a dummy and custom Solana on-chain transaction request which adds references to the transactions and based on other transaction data is able to calculate a credit score for Solana Ecosystem users.
How we built it
On-chain: Solana Custom Transaction: TypeScript (big thx to the support of Solana Team in this part), Phantom wallets [https://github.com/l-vicen/solana-pay/tree/master/core]
Middle: Helius, Python (Streamlit framework), Anaconda3, GoogleAPI&Sheets. (Serverless approach), (shell, .json et al.) [https://l-vicen-helius-listener-listener-7y4921.streamlit.app/] [https://github.com/l-vicen/helius-listener]
Frontend: Python (Streamlit framework), Anaconda3, GoogleAPI&Sheets. [https://l-vicen-solana-uis-app-ezy84t.streamlit.app/] [https://github.com/l-vicen/solana-uis]
Tech: Versel, Heroku and Streamlit Host App
Challenges we ran into
We lack webDev and web3 experience. So getting familiarized with TypeScript was a challenge. Naturally, the web3 in-depth know-how seems distant to students our age so we were no exception.
Accomplishments that we're proud of
Being able to ship something is rewarding. The amount of work was significant based on our experience but we had fun :)
What we learned
A lot, see prev. comments.
What's next for S-Moody
To the moon!