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Large-scale peer-to-peer loan consensus based on minimum cost consensus

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  • Huanhuan Zhang
  • Gang Kou
  • Yi Peng

Abstract

Large-scale decision-making, which involves a large number of participants, is common in practical applications. While cost is a crucial factor in large- scale decision-making, research on minimum cost consensus in group decision-making are mainly focused on a small number of experts. The goal of this paper is to expand the application of minimum cost consensus models to large-scale decision-making problems, and provide an approach for modeling and optimizing the cost in large-scale decision-making. This paper randomly collected a sample of 103 loans from one of the leading U.S. peer-to-peer loan platforms-Lending Club, and constructed several loan consensuses models. The minimum cost of loan consensus and changes of borrowers’ group opinions under such scenarios were studied. In addition, we discussed the effects of different loan consensus levels on the adjustments of interest rates and the consensus costs. The results showed that the proposed models can help Lending Club improve the efficiency of loan consensus reaching, and increase the rate of return of lenders. The proposed models provide a new way to coordinate the funds supply and demand of large-scale peer-to-peer lending, and help lenders and borrowers to reach a certain level of consensus on interest rates.

Suggested Citation

  • Huanhuan Zhang & Gang Kou & Yi Peng, 2022. "Large-scale peer-to-peer loan consensus based on minimum cost consensus," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(10), pages 2326-2337, October.
    • Handle: RePEc:taf:tjorxx:v:73:y:2022:i:10:p:2326-2337
    DOI: 10.1080/01605682.2021.1981782
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