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Classification methods applied to credit scoring: Systematic review and overall comparison · Study

ReviewClassification methods applied to credit scoring: Systematic review and overall comparison

Francisco Louzada2016

OA

Reviewgreen2016

Classification methods applied to credit scoring: Systematic review and overall comparison

Francisco Louzada · Anderson Ara · Guilherme Barreto Fernandes

68 citations·0/0 files stored·Surveys in Operations Research and Management Science

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Financial Distress and Bankruptcy Prediction Credit Risk and Financial Regulations Imbalanced Data Classification Techniques

Abstract

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Citations in this library

Stored only when both papers are in the corpus — 68 citations exist upstream.

References

1965Fuzzy sets 1991Content-Analysis Research: An Examination of Applications with Directives for Improving Research Reliability and Objectivity 2015Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research 1997Statistical Classification Methods in Consumer Credit Scoring: A Review 2000Neural network credit scoring models 2003Benchmarking state-of-the-art classification algorithms for credit scoring 2006Credit scoring with a data mining approach based on support vector machines 2007Using neural network ensembles for bankruptcy prediction and credit scoring

Cited by

2020A two-stage fuzzy neural approach for credit risk assessment in a Brazilian credit card company 2017Solvency prediction for small and medium enterprises in banking 2023Feature Selection Engineering for Credit Risk Assessment in Retail Banking 2023Machine learning and credit risk: Empirical evidence from small- and mid-sized businesses 2020Deep Neural Networks for Behavioral Credit Rating 2019Using reinforcement learning to optimize the acceptance threshold of a credit scoring model

Details

Year2016

Typereview

Published2016-11-26

VenueSurveys in Operations Research and Management Science

ISSN-L1876-7354

Languageen

Citations68

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

Identifiers

doi10.1016/j.sorms.2016.10.001

openalex_workW2270718652

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