PREDICTING BANKRUPTCY USING ARTIFICIAL INTELLIGENCE: THE CASE OF THE ENGINEERING INDUSTRY
PREDICTING BANKRUPTCY USING ARTIFICIAL INTELLIGENCE: THE CASE OF THE ENGINEERING INDUSTRY

Summary/Abstract: Bankruptcy prediction is a powerful early-warning tool and plays a crucial role in various aspects offinancial and business management. It is vital forsafeguarding investments, maintaining financial stability,making informed credit decisions, and contributing to theoverall health of the economy. This paper aims to developbankruptcy prediction models for the Slovak engineeringindustry and to compare their effectiveness. Predictionsare generated using the classical logistic regression (LR)method as well as artificial intelligence (AI) techniques(artificial neural networks (ANN) and support vectormachines (SVM)). Research sample consists of 825businesses operating in the engineering industry(Manufacture of machinery and equipment n.e.c.;Manufacture of motor vehicles, trailers and semi-trailers;Manufacture of other transport equipment). The selectionof eight financial indicators is grounded in prior researchand existing literature. The results show high accuracy forall used methods. The SVM outcomes indicate a level ofaccuracy on the test set that is nearly indistinguishablefrom that of the ANN model. The use of AI techniquesdemonstrates their effective predictive capabilities andholds a significant position within the realm of tools forforecasting bankruptcy.

• Details
• Contents