A literature review on the application of evolutionary computing to credit scoring
By Ana Isabel Marqués, Vicente García, José Salvador Sánchez. 2013
106 citations recorded by the source corpus.
Subfields: Accounting, Finance, Ocean Engineering
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Accounting
- Begoña Gutiérrez-Nieto
- Carlos Serrano-Cinca
- Luz López-Palacios
- Qinghua Huang
- A. Ozbayoglu
- Omer Berat Sezer
- Kai-Yu He
- M. Ugur Gudelek
In Finance
- M. Ugur Gudelek
- A. Ozbayoglu
- Omer Berat Sezer
- Begoña Gutiérrez-Nieto
- Carlos Serrano-Cinca
- Luz López-Palacios
- Qinghua Huang
- Kai-Yu He
In Ocean Engineering
Citations in the corpus
- Deep Learning for Financial Applications : A Survey (2020, background): “[89] focused only on Evolutionary Computation (EC) Models for credit scoring implementations.”
- Determinants of Default in P2P Lending (2015, background): “However, most credit scoring models have an empirical nature [30], [48], [49].”
- Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2014, methodology): “[78] summarized the application of evolution computing to credit scoring, which included classification, variable selection, and parameter optimization.”
- Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation (2015, background): “Credit risk evaluation is by its own a vast domain, encompassing a large number of research publications within banking and spread through the last twelve years (e.g., Marqués et al. (2012)).”