Abstract
This paper aims to compare the accuracy of financial ratios, tax arrears and annual report submission delays for the prediction of bank loan defaults. To achieve this, 12 variables from these three domains are used, while the study applies a longitudinal whole-population dataset from an Estonian commercial bank with 12,901 observations of defaulted and non-defaulted firms. The analysis is performed using statistical (logistic regression) and machine learning (neural networks) methods. Out of the three domains used, tax arrears show high prediction capabilities for bank loan defaults, while financial ratios and reporting delays are individually not useful for that purpose. The best default prediction accuracies were 83.5% with tax arrears only and 89.1% with all variables combined. The study contributes to the extant literature by enhancing the bank loan default prediction accuracy with the introduction of novel variables based on tax arrears, and also by indicating the pecking order of satisfying creditors’ claims in the firm failure process.
Highlights
Business failure prediction is a constantly evolving stream of literature
The study contributes to the extant literature by enhancing the bank loan default prediction accuracy with the introduction of novel variables based on tax arrears, and by indicating the pecking order of satisfying creditors’ claims in the firm failure process
The study aimed to compare the accuracy of financial ratios, tax arrears and annual report submission delays for predicting bank-loan defaults
Summary
Business failure prediction is a constantly evolving stream of literature. The research field is important because when companies fail, they can have a significantly negative social and financial impact on owners, employees, creditors, clients and other stakeholders of the failed businesses, and to economies and societies in general (Alaka et al 2018; CamachoMiñano et al 2015; Wu 2010). Business failure as a phenomenon has a broad range of definitions. Business failure could mean bond default, bank loan default, delisting of a company, government intervention and liquidation (Altman and Narayanan 1997). The most commonly used definition in failure-prediction studies is bankruptcy; it is only one of the many negative events in the business failure process
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