Risk Assessment of Polish Joint Stock Companies: Prediction of Penalties or Compensation Payments

Aleksandra Szymura
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Aleksandra Szymura: Department of Econometrics and Operational Research, Wroclaw University of Economics and Business, Komandorska 118/120, 53-345 Wroclaw, Poland

Risks, 2022, vol. 10, issue 5, 1-22

Abstract: Corporate misconduct is a huge and widespread problem in the economy. Many companies make mistakes that result in them having to pay penalties or compensation to other businesses. Some of these cases are so serious that they take a toll on a company’s financial condition. The purpose of this paper was to create and evaluate an algorithm which can predict whether a company will have to pay a penalty and to discover what financial indicators may signal it. The author addresses these questions by applying several supervised machine learning methods. This algorithm may help financial institutions such as banks decide whether to lend money to companies which are not in good financial standing. The research is based on information contained in the financial statements of companies listed on the Warsaw Stock Exchange and NewConnect. Finally, different methods are compared, and methods which are based on gradient boosting are shown to have a higher accuracy than others. The conclusion is that the values of financial ratios can signal which companies are likely to pay a penalty next year.

Keywords: machine learning; supervised learning; classification; corporate finance; financial analysis; financial indicators (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2022
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