A model for assessing financial risk and economic development of companies based on heterogeneous data

Financial risk has a far-reaching impact, not only on a company's development but also on the broader economic development of society as a whole. Consequently, the assessment of a company's financial risk holds significant importance. Presently, researchers have explored various methods to evaluate financial risk. However, a majority of these methods lack the integration of fuzzy sets in quantitative analysis and fail to account for historical data from recent years. To address these deficiencies, this research introduces a novel model for assessing financial risk in companies. This model is based on heterogeneous multi-criteria decision making (MCDM) and leverages historical data. Furthermore, it incorporates both subjective and objective indicators in the financial risk assessment index system, merging fuzzy theory with quantitative data analysis. The model also encompasses valuation information derived from historical financial records of the company, credit rating agencies, and decisions made by stakeholders, incorporating deterministic numbers, triangular fuzzy numbers, and neutrosphere numbers. To determine the ranking of companies concerning their financial risk, a preference technique based on similarity to the ideal solution (TOPSIS) is employed. In conclusion, an empirical study on financial risk assessment for companies is conducted, revealing that the proposed model effectively and reliably minimizes financial risk for the company, as demonstrated through comparative analysis and sensitivity analysis

Keywords:

Financial risk , economic development , heterogeneous data , TOPSIS , fuzzy