Non-compliance to Benford distribution as the portfolio default rate determinant in online retail lending

H. Penikas
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Abstract

There is large online lending growth in volume world-wide. The credit risk concerns point to the fact that most of these loans might be used to redeem earlier borrowed funds. However, the true reasons for online borrowing and lending are unavailable. Benford law is one of the tools used by auditors to monitor how suspicious the transaction is. That is why I wish to study one of the publicly available lending portfolios. Our objective is to trace associativity of compliance to Benford law and reported default rates. I find that MAE is a more statistically significant determinant of the country portfolio default rate, than RMSE. Moreover, the least creditworthy portfolios seem to be those with the MAE around 52–56%, while the closest to Benford and the least adjacent distribution do not demonstrate that large default rates.
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不遵守Benford分布作为在线零售贷款组合违约率的决定因素
全球范围内的在线贷款数量大幅增长。对信贷风险的担忧表明,这些贷款中的大部分可能被用于赎回之前借入的资金。然而,网上借贷的真实原因尚不清楚。Benford法是审计师用来监控交易可疑程度的工具之一。这就是为什么我想研究一个公开的贷款组合。我们的目标是追踪遵守本福德法律和报告违约率的关联性。我发现MAE是国家投资组合违约率的一个更具统计意义的决定因素,而不是RMSE。此外,信誉最差的投资组合似乎是MAE约为52-56%的投资组合,而最接近Benford和分布最不相邻的投资组合并没有显示出较大的违约率。
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来源期刊
Model Assisted Statistics and Applications
Model Assisted Statistics and Applications Mathematics-Applied Mathematics
CiteScore
1.00
自引率
0.00%
发文量
26
期刊介绍: Model Assisted Statistics and Applications is a peer reviewed international journal. Model Assisted Statistics means an improvement of inference and analysis by use of correlated information, or an underlying theoretical or design model. This might be the design, adjustment, estimation, or analytical phase of statistical project. This information may be survey generated or coming from an independent source. Original papers in the field of sampling theory, econometrics, time-series, design of experiments, and multivariate analysis will be preferred. Papers of both applied and theoretical topics are acceptable.
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