MITIGATING LOAN ASSOCIATED FINANCIAL RISK USING BLOCKCHAIN BASED LENDING SYSTEM

Saha RENO

reno.saha39@gmail.com
Bangladesh Army International University of Science and Technology, Dept. of CSE, Cumilla (Bangladesh)

Sheikh Surfuddin Reza Ali CHOWDHURY


Bangladesh Army International University of Science and Technology, Dept. of CSE, Cumilla (Bangladesh)

Iqramuzzaman SADI


(Bangladesh)

Abstract

Lending systems in real world are not much secure and reliable as the borrower and third parties involved in this aspect may create various deceitful situations. Blockchain is a secure system where the utilization of smart contract can avoid deceptive phenomena involved in lending but the decline in exchange rate of cryptocurrency can create the opportunity to pay back less than the borrowed amount in terms of fiat money. In this paper, a blockchain and smart contract-based lending framework is designed which requires the borrower to provide Ethereum Request for Comments (ERC)-20 standard tokens as collateral to mitigate the associated risks. The smart contract feature is utilized to automate the system without any third-party management. Besides, transaction stored in the blocks creates transparency among the users of the system. To tackle the aforementioned issues, ERC-20 token value is increased periodically and the instability of the exchange rate is surveilled by the system. By the end of this paper, some test cases and charts relevant to the data set are evaluated to assess the effectiveness of the system.


Keywords:

Blockchain, Ethereum, Smart Contract, ERC-20 Tokens, Loan Default

Download


Published
2021-06-30

Cited by

RENO, S., CHOWDHURY, S. S. R. A. ., & SADI, I. (2021). MITIGATING LOAN ASSOCIATED FINANCIAL RISK USING BLOCKCHAIN BASED LENDING SYSTEM. Applied Computer Science, 17(2), 100–126. https://doi.org/10.23743/acs-2021-16

Authors

Saha RENO 
reno.saha39@gmail.com
Bangladesh Army International University of Science and Technology, Dept. of CSE, Cumilla Bangladesh

Authors

Sheikh Surfuddin Reza Ali CHOWDHURY 

Bangladesh Army International University of Science and Technology, Dept. of CSE, Cumilla Bangladesh

Authors

Iqramuzzaman SADI 

Bangladesh

Statistics

Abstract views: 185
PDF downloads: 100


License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.