Wykorzystanie branżowego wskaźnika ryzyka kredytu kupieckiego w polskich realiach gospodarczych w latach 2013–2023
The Usefulness of the Industry Trade Credit Risk Indicator in the Polish Economic Realities in 2013–2023

Summary/Abstract: Purpose: The aim of this article is to introduce the methodology for creating a synthetic industry indicator of trade credit risk (PICM Risk Index©), which will be useful in forecasting the number of defaults in economic sectors. In particular, the PICM Risk Index© indicator is to be characterized by the smallest possible forecast error and is to be variable in monthly periods.Methodology: In the construction of the indicator, the economic situation research of the Central Statistical Office was used. The research hypotheses assumed were that the indicator shows a statistically significant relationship with insolvencies in the sectors of the economy, i.e. at least to a high degree in the meaning of the correlation classification according to Guilford. In the proposed methodology, the indicator shows greater effectiveness as a leading measure, i.e. the forecast error is the smallest for predictions one year in advance.Findings: The proposed indicator is highly or very highly correlated with industry default statistics. In addition, the PICM Risk Index© is characterized by a smaller forecast error for predicting the number of defaults one year in advance.Research limitations/implications: Forecasting corporate bankruptcy is a major challenge due to the considerable complexity of the conditions for conducting business activity and the dynamic variability of the micro- and macroeconomic environment. The selected input data in the construction of the proposed indicator, although commonly used due to their high cognitive value confirmed by numerous studies, are also criticized due to their nature referred to as “soft” (qualitative) data. Therefore, the topic discussed in the article should be the beginning of research to which a reasonable number of other input variables can be included. The article shows how generally available information can be the basis for building an effective and at the same time simple to construct credit risk assessment indicator for economic sectors. Saving time in the process of holistic credit analysis and the accuracy of the assessment are also significant. Both of these factors can be the subject of separate analyses, but there is no doubt that they are very important for credit analysis practitioners.Originality/value: The article identifies two areas of research gap and proposes an indicator PICM Risk Index©, which in its presented form has not yet functioned in Polish and international realities. The indicator is a very effective element of a holistic credit analysis, supplementing the credit analysis of a single enterprise with a measure of the risk of the industry in which the enterprise operates.Methodology: In the construction of the indicator, the economic situation research of the Central Statistical Office was used. The research hypotheses assumed were that the indicator shows a statistically significant relationship with insolvencies in the sectors of the economy, i.e. at least to a high degree in the meaning of the correlation classification according to J. Guilford. In the proposed methodology, the indicator shows greater effectiveness as a leading measure, i.e. the forecast error is the smallest for predictions one year in advance.Findings: The proposed indicator is highly or very highly correlated with industry default statistics. In addition, the PICM Risk Index© is characterized by a smaller forecast error for predicting the number of defaults one year in advance.Research limitations/implications: Forecasting corporate bankruptcy is a major challenge due to the considerable complexity of the conditions for conducting business activity and the dynamic variability of the micro- and macroeconomic environment. The selected input data in the construction of the proposed indicator, although commonly used due to their high cognitive value confirmed by numerous studies, are also criticized due to their nature referred to as "soft" (qualitative) data. Therefore, the topic discussed in the article should be the beginning of research to which a reasonable number of other input variables can be included. The article shows how generally available information can be the basis for building an effective and at the same time simple to construct credit risk assessment indicator for economic sectors. Saving time in the process of holistic credit analysis and the accuracy of the assessment are also significant. Both of these factors can be the subject of separate analyses, but there is no doubt that they are very important for credit analysis practitioners.Originality/value: The article identifies two areas of research gap and proposes an indicator PICM Risk Index©, which in its presented form has not yet functioned in Polish and international realities. The indicator is a very effective element of a holistic credit analysis, supplementing the credit analysis of a single enterprise with a measure of the risk of the industry in which the enterprise operates.

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