The perfect bail-in: Financing without banks using Peer-To-Peer Lending

Stathis Polyzos, Aristeidis Samitas, G. Rubbaniy
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引用次数: 1

Abstract

This paper explores the potential outcomes of using peer-to-peer lenders in financing economic activity. Combining a random regression forest, a machine-learning process, with an agent-based model, we perform simulations on artificial economies with various degrees of adoption of peer-to-peer lending. We find that as peer-to-peer lenders proliferate, there is increased financial instability, lower GDP and higher unemployment. On the other hand, peer-to-peer lending increases the total volume of loans given out, but demonstrates a preference towards consumer loans (over corporate loans), which has a negative effect in the long run. Finally, introducing peer-to-peer lenders increases the access of the “unbankable” population to services which conventional banking is not able to offer within the extant regulatory framework. Our results can help policymakers as they address the issue of regulation in the peer-to-peer finance industry.
完美的内部纾困:没有银行的融资,使用点对点贷款
本文探讨了在经济活动融资中使用点对点贷款的潜在结果。结合随机回归森林,机器学习过程和基于代理的模型,我们对不同程度采用点对点借贷的人工经济进行了模拟。我们发现,随着p2p贷款机构的激增,金融不稳定性增加,GDP下降,失业率上升。另一方面,个人对个人贷款增加了发放的贷款总量,但表现出对消费贷款(而不是企业贷款)的偏好,这从长远来看会产生负面影响。最后,引入点对点贷款增加了“无法获得银行服务”的人群获得传统银行在现有监管框架内无法提供的服务的机会。我们的研究结果可以帮助决策者解决点对点金融行业的监管问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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