MODELING THE ENTERPRISE FINANCIAL RESILIENCE BASED ON OPEN SOURCE DATABASES USING APPLICATION PROGRAMMING INTERFACE AND PYTHON METHODS
DOI:
https://doi.org/10.15407/economyukr.2024.05.068Keywords:
financial resilience; methods of mathematical and economic analysis; modeling; crisis conditionsAbstract
The importance of financial resilience for the successful functioning of the enterprise and maintaining its competitiveness is undeniable. Therefore, appropriate analysis helps predict risks, determine optimal management strategies, and serve as a basis for making informed decisions regarding investments and lending. The essential aspects of financial resilience, such as the structure of assets and sources of financing, determine its level.
Methods of mathematical and economic analysis, such as discriminant analysis and the Altman model, were used to study the financial resilience of companies. A particular emphasis is placed on using open data and programming, in specific API and the Python programming language, for modeling and analyzing the state of enterprises. The importance of using programming interfaces (APIs) to obtain specific information from other software tools is considered. It is noted that an API defines an interface that facilitates interaction between software products. The primary attention is paid to calls of functions in programs that contribute to the performance of specific tasks through the exchange of data and functionality. It is noted that Python provides the necessary libraries for working with the API and using the obtained data for analysis and visualization. The implementation algorithm for the enterprise financial resilience modeling program is described based on the case of using the Financial Modeling Prep API to calculate the Z-score according to the Altman model for Apple Inc. for the period from 2020 through 2023.
Apple Inc.'s case study shows that API use in financial resilience modeling allows for obtaining relevant and reliable data, facilitating analysis, and contributing to effective strategic decision-making. It is noted that this approach not only speeds up the research process but also makes it more accessible to various companies.
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