Are machine learning models more effective than logistic regressions in predicting bank credit risk? : an assessment of the Brazilian financial markets
Alex Cerqueira Pinto, Alexandre Xavier Ywata de Carvalho, Mathias Schneid Tessmann and Alexandre Vasconcelos Lima
| Year of publication: |
2024
|
|---|---|
| Authors: | Pinto, Alex Cerqueira ; Carvalho, Alexandre Ywata de ; Tessmann, Mathias Schneid ; Lima, Alexandre Vasconcelos |
| Published in: |
International journal of monetary economics and finance : IJMEF. - Genève [u.a.] : Inderscience Enterprises, ISSN 1752-0487, ZDB-ID 2471959-6. - Vol. 17.2024, 1, p. 29-48
|
| Subject: | credit risk in Brazilian banks | credit risk measurement | empirical evidence in finance and banking | machine learning to detect credit risk | Kreditrisiko | Credit risk | Brasilien | Brazil | Künstliche Intelligenz | Artificial intelligence | Bankrisiko | Bank risk | Kreditgeschäft | Bank lending | Risikomanagement | Risk management | Basler Akkord | Basel Accord |
Online Resource
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1504/IJMEF.2024.137545 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10015066103