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To supervise or to self‑supervise:a machine learning based comparison on credit supervision 被引量:3
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作者 JoséAmérico Pereira Antunes 《Financial Innovation》 2021年第1期562-582,共21页
This study investigates the need for credit supervision as conducted by on-site banking supervisors.It builds on a real bank on-site credit examination to compare the performance of a hypothetical self-supervision app... This study investigates the need for credit supervision as conducted by on-site banking supervisors.It builds on a real bank on-site credit examination to compare the performance of a hypothetical self-supervision approach,in which banks themselves assess their loan portfolios without external intervention,with the on-site banking supervision approach of the Central Bank of Brazil.The experiment develops two machine learning classification models:the first model is based on good and bad ratings informed by banks,and the second model is based on past on-site credit portfolio examinations conducted by banking supervision.The findings show that the overall performance of the on-site supervision approach is consistently higher than the performance of the self-supervision approach,justifying the need for on-site credit portfolio examination as conducted by the Central Bank. 展开更多
关键词 Bank supervision Machine learning Loan loss provisions On-site credit supervision
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