FINANCIAL DISTRESS AND INSOLVENCY PREDICTION IN GEORGIAN CONSTRUCTION COMPANIES
Authors: Tamar Kapanadze Bakradze
DOI: 10.5281/zenodo.17423725
Published: April 2024
Abstract
<p><em>Insolvency prediction is a critical aspect of assessing a company’s financial health, enabling the identification of risk factors and early warning signals for potential financial distress. This study focuses on construction companies in small and developing countries, with a particular emphasis on Georgia, aiming to evaluate their financial health and predict insolvency. Using financial statements of individual companies, key financial ratios were analyzed to assess financial stability and inform the development of an insolvency prediction model. The model employs logistic regression to estimate the probability of insolvency, achieving an accuracy rate of 90%. This high level of predictive accuracy demonstrates the model’s effectiveness in forecasting financial distress in the construction sector. As one of the first studies to use publicly accessible financial data for insolvency prediction in Georgia, the research provides valuable insights for both academics and practitioners. The model can be applied to construction companies in other countries with similar economic and industry characteristics, supporting early intervention and informed decision-making to mitigate financial risk.</em></p>
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