ACS Applied Computer Science

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MITIGATING LOAN ASSOCIATED FINANCIAL RISK USING BLOCKCHAIN BASED LENDING SYSTEM

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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.

  • APA 7th style
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
  • Chicago style
Reno, Saha, Sheikh Surfuddin Reza Ali Chowdhury, and Iqramuzzaman Sadi. "Mitigating Loan Associated Financial Risk Using Blockchain Based Lending System." Applied Computer Science 17, no. 2 (2021): 100-126.
  • IEEE style
S. Reno, S. S. R. A. Chowdhury, and I. Sadi, "Mitigating loan associated financial risk using blockchain based lending system," Applied Computer Science, vol. 17, no. 2, pp. 100-126, 2021, doi: 10.23743/acs-2021-16.
  • Vancouver style
Reno S, Chowdhury SSRA, Sadi I. Mitigating loan associated financial risk using blockchain based lending system. Applied Computer Science. 2021;17(2):100-126.