Die Hard: Probability of Default and Soft Information

Gabbi, Giampaolo; Giammarino, Michele; Matthias, Massimo

doi:10.3390/risks8020046

Cited by 9 publications

(2 citation statements)

References 23 publications

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“…As explained earlier, in failure-prediction literature, the term "non-financial variable" is commonly used by researchers for various variables other than financial ratios calculated by using financial statements. Prediction models that include non-financial variables such as previous payment patterns (Back 2005), corporate governance (Ciampi 2015), reporting and compliance (Altman et al 2010), balanced scorecard information (Gabbi et al 2020) and tax arrears (Lukason and Andresson 2019) have usually outperformed classical prediction models based solely on financial variables. Non-financial information, such as previous payment history, holds more updated information compared to financial data (Laitinen 2011).…”

Section: Financial and Non-financial Variables For Firm Failure Predictionmentioning

confidence: 99%

What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains

Kohv

Lukason

2021

Risks

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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.

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Section: Financial and Non-financial Variables For Firm Failure Predictionmentioning

confidence: 99%

What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains

Kohv

Lukason

2021

Risks

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“…Current threats and risk management systems are key CSR factors for Stakeholders and the country's economy. Polish and EU economic disruptions may also affect energy company performance; fuels, gas, and mining companies; project subcontractors, and customers e.g., [20][21][22][23]. It is thus important to identify new energy company risks.…”

Section: Introductionmentioning

confidence: 99%

A Model of Risk Information Disclosures in Non-Financial Corporate Reports of Socially Responsible Energy Companies in Poland

2022

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Risk management is critical for corporate finance management systems, in addition to corporate social responsibility (CSR) and sustainable development (SD) programs. Stakeholders need risk information to make informed judgments as to their involvement. No studies exist to date concerning disclosure of non-financial and financial risks in corporate annual statements and Polish strategic sector company reports. The authors sought to determine whether energy companies disclosed risks in non-financial annual reports in 2011–2020 (e.g., CSR, integrated, and board activity reports), and whether one can assess threats, including business activity risks and SD, based on these reports. We assessed the reports of all large Polish energy companies on a three- and five-degree scale to develop a model for risk information disclosures. We have three key empirical findings. Only half the analysed companies disclose annual financial data, threats, and risks. Less than half have implemented and operate enterprise risk management systems. The current ‘soft’ regulatory solutions give energy companies appreciable risk disclosure options, which often is counterproductive. We suggest developing a single integrated European Union (EU) regulation (e.g., directives, standards, or official principles) for non-financial risk disclosures. Our model classifies Polish energy company risks to business activity operations and risk management systems. Other sectors can use this universal model. Our results constitute progress in identifying company risks and may encourage continuing studies of other energy companies, especially in Central and Eastern Europe (CEE), which should be intensively developed. Research should also occur in other strategic sectors.

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Financial Crisis 2020: Problems and Elements of Forecasting

Matveeva

2021

Post-Covid Economic Revival, Volume I

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Die Hard: Probability of Default and Soft Information

Cited by 9 publications

References 23 publications

What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains

What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains

A Model of Risk Information Disclosures in Non-Financial Corporate Reports of Socially Responsible Energy Companies in Poland

Financial Crisis 2020: Problems and Elements of Forecasting

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