Maestría en Ciencias de los Datos y Analítica · 2024

Modelo predictivo de insolvencia empresarial para las pymes en Colombia

Business insolvency has an economic impact on the affected company and, directly and indirectly, on its suppliers of goods and services. This ends up affecting the general population, who are the consumers of these goods and services. Therefore, it is important to analyze and study the possible factors that lead a company to enter a situation of economic insolvency. In accordance with the above, the objective of this work is to predict business insolvency in the Colombian context for SMEs. Likewise, use will be made of the financial data available from the Superintendency of Companies in the year 2021 and the companies that entered into a situation of economic insolvency in the year 2023. In this way, through financial indicators, it will be possible to construct the explanatory variables. of economic insolvency and achieve a predictive model of economic insolvency. This work is approached as follows: first, information is extracted from the Superintendency of Companies for SMEs in 2021 and companies that entered economic insolvency in 2023 to obtain our objective variable. Then, based on the data obtained, the financial ratios necessary for this study are calculated, using the financial statements of these companies corresponding to the year 2021. Next, the exploratory data analysis is carried out to obtain a broader knowledge of the set. of data and analyze correlation issues between variables, among other aspects. Finally, several machine learning models are designed to determine which one is most appropriate for the case study

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