Politická ekonomie 2018, 66(6):689-708 | DOI: 10.18267/j.polek.1226

Využitie skóringových modelov pri predikcii defaultu ekonomických subjektov v Slovenskej republike

Matúš Mihalovič
Matúš Mihalovič (matus.mihalovic@gmail.com), Ekonomická univerzita Bratislava, Podnikovohospodárska fakulta Košice

Applicability of Scoring Models in Firms' Default Prediction. The Case of Slovakia

Bankruptcy prediction has long been regarded as a critical topic within the academic and banking community. To the best of our knowledge, no previous study in the Slovak Republic has attempted to develop a bankruptcy prediction model putting together statistical and artificial intelligence approaches performed on a such an amount of data. This paper seeks to fill this gap. Our aim is to develop a hybrid bankruptcy prediction model using a genetic algorithm in the process of training a neural network (GA-NN). The research data set comprises a balanced sample of both healthy and bankrupt firms operating in Slovakia in the period from 2014 to 2017. Financial information regarding a firm's financial situation are acquired from the Finstat database, which stores annual reports. For the purpose of comparing the classification accuracy of the proposed GA-NN model, two more models are constructed, namely BP-NN (back-propagation neural network model) as well as MDA (multiple discrimination model). The results gained by utilizing these models suggest the superiority of the developed GA-NN model to both BP-NN and MDA models in terms of prediction performance.

Keywords: bankruptcy prediction, genetic algorithms, hybrid classifier, neural networks, pre-diction performance, scoring model, GA-NN model, default, decision trees
JEL classification: C45, C53, G32, G33, M21

Received: December 18, 2017; Accepted: September 18, 2018; Published: December 1, 2018  Show citation

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Mihalovič, M. (2018). Applicability of Scoring Models in Firms' Default Prediction. The Case of Slovakia. Politická ekonomie, 66(6), 689-708. doi: 10.18267/j.polek.1226
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