Estimation of the Default Probability for Housing and Utilities Services Management Companies in Russia

The aim of this Master Thesis is the creation of a precise instrument of bankruptcy prediction for the Housing and Utilities Services Management Companies. Such companies play a great role in the everyday life of Russian estate owners, being the intermediaries between the tenants and the suppliers of the resources (gas, electricity, water etc.). Financial failures of management companies affect several groups of stakeholders: the tenants, the resources providers and the management companies’ employees. All the mentioned groups face different negative outcomes of management companies’ bankruptcies. That is why the creation of an instrument of bankruptcy risk estimation is very important. There are many studies, devoted to bankruptcy prediction in different industries, but it seems, that for now none of them provides an acceptable accuracy. This statement is contributed by the analysis, carried out during the Master Thesis preparation. A set of Housing & Utilities Services Management companies was used for the creation of a new classification model, based on Logit Regression Analysis and Machine Learning. The results turned to be rather promising, as the author managed to receive 84% classification accuracy of the model. The findings of this Master Thesis can be used by a variety of management companies’ stakeholders for predicting financial distress.