Propension to customer churn in a financial institution: a machine learning approach

Author:

de Lima Lemos Renato Alexandre,Silva Thiago Christiano,Tabak Benjamin MirandaORCID

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference65 articles.

1. Agarwal P, Nieto JJ, Ruzhansky M, Torres DF (2021) Analysis of infectious disease problems (Covid-19) and their global impact. Springer, New York

2. Ahmed M, Afzal H, Siddiqi I, Amjad M, Khurshid K (2020) Exploring nested ensemble learners using overproduction and choose approach for churn prediction in telecom industry. Neural Comput Appl 32:3237–3251

3. Au T, Ma G, Li S (2003) Applying and evaluating models to predict customer attrition using data mining techniques. J Comp Int Manag 6(1):10–22

4. Avon V (2016) Machine learning techniques for customer churn prediction in banking environments. Doctorate Thesis. Universita degli Studi di, Padova, Italy

5. BACEN (2018) Relatório de Economia Bancária (Banking Report). Banco Central do Brasil. https://www.bcb.gov.br/content/publicacoes/relatorioeconomiabancaria/reb_2018.pdf

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