Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art
AA Montevechi, R de Carvalho Miranda… - … Applications of Artificial …, 2024 - Elsevier
Ensuring financial stability necessitates responsible credit granting, so lending institutions
maintain sufficient regulatory capital to withstand losses from defaults. Classification …
maintain sufficient regulatory capital to withstand losses from defaults. Classification …
Combining corporate governance indicators with stacking ensembles for financial distress prediction
In this paper, we use a stacking ensemble to construct a bankruptcy prediction model. We
collect a comprehensive list of 40 financial ratios (FRs) and 21 corporate governance …
collect a comprehensive list of 40 financial ratios (FRs) and 21 corporate governance …
New hybrid data mining model for credit scoring based on feature selection algorithm and ensemble classifiers
J Nalić, G Martinović, D Žagar - Advanced Engineering Informatics, 2020 - Elsevier
The aim of this paper is to propose a new hybrid data mining model based on combination
of various feature selection and ensemble learning classification algorithms, in order to …
of various feature selection and ensemble learning classification algorithms, in order to …
Peer level credit rating: an extended plugin for credit scoring framework
M Rudra Kumar, VK Gunjan - ICCCE 2021: Proceedings of the 4th …, 2022 - Springer
Credit scores hold significant importance for the people to avail credit from the banking and
fin-tech companies. With the increasing trends of using the contemporary model of credit …
fin-tech companies. With the increasing trends of using the contemporary model of credit …
Cost-sensitive stacking ensemble learning for company financial distress prediction
S Wang, G Chi - Expert Systems with Applications, 2024 - Elsevier
Financial distress prediction (FDP) is a topic that has received wide attention in the finance
sector and data mining field. Applications of combining cost-sensitive learning with …
sector and data mining field. Applications of combining cost-sensitive learning with …
Business-oriented feature selection for hybrid classification model of credit scoring
G Chornous, I Nikolskyi - … Conference on Data Stream Mining & …, 2018 - ieeexplore.ieee.org
Application of predictive models on the basis of data mining confirmed its expediency in
solving many economic problems. One of the crucial issues is the assessment of the …
solving many economic problems. One of the crucial issues is the assessment of the …
Research on prediction of power market credit system based on linear model and improved BP neural network
D Li, M Wang, Q Yan - Soft Computing, 2023 - Springer
With the continuous economic growth, the number of power customers has increased
significantly, and consumers in the field of power marketing will inevitably have a credit …
significantly, and consumers in the field of power marketing will inevitably have a credit …
Mobility Prediction Algorithms for Handover Management in Heterogeneous LiFi and RF Networks: An Ensemble Approach
Abstract Light Fidelity (LiFi) is a communication technology that operates in the Visible Light
(VL) region, using light as a medium to enable ultra-high-speed communication. The …
(VL) region, using light as a medium to enable ultra-high-speed communication. The …
Predição de tendências em séries financeiras utilizando metaclassificadores
Neste trabalho foi desenvolvido um metaclassificador baseado em métodos de inteligência
computacional para prever tendências em séries temporais financeiras. O kernel do …
computacional para prever tendências em séries temporais financeiras. O kernel do …
Weather event prediction using combination of data mining algorithms
Weather event prediction offerings suitable from the obsolete occurrences as a main
gigantic obligation, since it depends on upon dissimilar constraints to forecast the destitute …
gigantic obligation, since it depends on upon dissimilar constraints to forecast the destitute …