Publication Date
Spring 2024
Degree Type
Master's Project
Degree Name
Master of Science in Computer Science (MSCS)
Department
Computer Science
First Advisor
Chris Pollett
Second Advisor
Thomas Austin
Third Advisor
Bhushan Sonawane
Keywords
DeFi, Blockchain, Ethereum, Smart Contracts
Abstract
Traditional banking systems act as intermediaries, assessing risks and profiting from interest rate differentials. Credit scores, provided by trusted bureaus, are commonly used to evaluate the creditworthiness of borrowers. Cryptocurrencies have emerged as a significant and innovative medium due to their decentralized nature, operating without reliance on a central authority, such as a government.
This report describes a project to implement the Autonomous Lending system on the Ethereum Platform (ALOE), as proposed in [1], aiming to seamlessly integrate traditional credit scoring methodologies for evaluating a borrower's risk of default. The objective of this project report is to establish a robust understanding of cryptocurrencies and the Ethereum platform and describe the implementation of pivotal components of the ALOE system, as presented by Austin, Potika, and Pollett in 2023. Specifically, the report aims to incorporate essential functionalities of the Credit Bureau Smart Contract (CBSC). This entails the creation of a Notary tasked with verifying borrowers using real-world FICO scores, SSNs, and Ethereum Addresses. The Notary further divides the user's identity
among various auditors and invokes the initializeLedger function to establish a credit score for the borrower. The CBSC plays a pivotal role in connecting lenders and borrowers. Finally, in cases of loan repayment failure, lenders have the option to engage auditors to disclose the client's identity.
Recommended Citation
Shimpi, Mayuri, "Credit Score-Based Lending System On the Ethereum Platform" (2024). Master's Projects. 1373.
https://scholarworks.sjsu.edu/etd_projects/1373
