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Secure Lending: Blockchain and Prospect Theory-Based Decentralized Credit Scoring Model

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dc.contributor.author Chamola, Vinay
dc.date.accessioned 2023-03-16T11:19:38Z
dc.date.available 2023-03-16T11:19:38Z
dc.date.issued 2020-10
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/9044411
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9795
dc.description.abstract Credit scoring is a rigorous statistical analysis carried out by lenders and other third parties to access an individual's creditworthiness. Lenders use credit scoring to estimate the degree of risk in lending money to an individual. However, credit score evaluation is primarily based on a transaction record, payment history, professional background, etc. sourced from different credit bureaus. So, evaluating a credit score is a laborious and tedious task involving a lot of paperwork. In this paper, we propose how blockchain can provide the solution to decentralized credit scoring evaluation and reducing the amount of dependence of paperwork. Lending money is not always objective but subjective to every lender. The decision of lending involves different levels of risk and uncertainty, depending on their perspective. This paper uses the prospect theory to model the optimal investment strategy for different risk vs. return scenarios. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEE en_US
dc.subject Blockchain en_US
dc.subject Behavioural economics en_US
dc.subject Credit score en_US
dc.subject Prospect theory en_US
dc.subject Security en_US
dc.title Secure Lending: Blockchain and Prospect Theory-Based Decentralized Credit Scoring Model en_US
dc.type Article en_US


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