Bankruptcy prediction using ensemble of autoencoders optimized by genetic algorithm.

ABSTRACT: The prediction of imminent bankruptcy for a company is important to banks, government agencies, business owners, and different business stakeholders. Bankruptcy is influenced by many global and local aspects, so it can hardly be anticipated without deeper analysis and economic modeling knowledge. To make this problem even more challenging, the available bankruptcy datasets are usually imbalanced since even in times of financial crisis, bankrupt companies constitute only a fraction of all operating businesses. In this article, we propose a novel bankruptcy prediction approach based on a shallow autoencoder ensemble that is optimized by a genetic algorithm. The goal of the autoencoders is to learn the distribution of the majority class: going concern businesses. Then, the bankrupt companies

SUBMITTER: Kanasz R 

PROVIDER: S-EPMC10280414 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature