Estimating credit and profit scoring of a Brazilian credit union with logistic regression and machine-learning techniques

Estimating credit and profit scoring of a Brazilian credit union with logistic regression and machine-learning techniques

Purpose – Although credit unions are nonprofit organizations, their objectives depend on the efficient management of their resources and credit risk aligned with the principles of the cooperative doctrine. This paper aims to propose the combined use of credit scoring and profit scoring to increase t...

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Bibliographic Details
Main Authors: Daniel Abreu Vasconcellos de Paula, Rinaldo Artes, Fabio Ayres, Andrea Maria Accioly Fonseca Minardi
Format: Article
Language:English
Published: Emerald Publishing 2019-07-01
Series:RAUSP Management Journal
Subjects:
credit unions
Online Access:https://www.emerald.com/insight/content/doi/10.1108/RAUSP-03-2018-0003/full/pdf?title=estimating-credit-and-profit-scoring-of-a-brazilian-credit-union-with-logistic-regression-and-machine-learning-techniques

Internet

https://www.emerald.com/insight/content/doi/10.1108/RAUSP-03-2018-0003/full/pdf?title=estimating-credit-and-profit-scoring-of-a-brazilian-credit-union-with-logistic-regression-and-machine-learning-techniques

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