Research Article

Hybrid Approach for the Financial Assessment of Companies using Fuzzy Multi-Criteria Decision-Making and Self-Organizing Maps

Volume: 13 Number: 2 July 1, 2024
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Hybrid Approach for the Financial Assessment of Companies using Fuzzy Multi-Criteria Decision-Making and Self-Organizing Maps

Abstract

This paper presents a 3-stage innovative approach for company assessment, integrating financial ratios with the Fuzzy Analytic Hierarchy Process (FAHP) and using an unsupervised artificial intelligence method, Self-Organizing Maps (SOM), for classification. Addressing the challenges of decision-making in resource allocation, the study combines accurate data with robust tools essential in turbulent economic times. FAHP, known for handling complex, uncertain information, is applied to refine the traditional company assessment methods by integrating different experts' opinions and conversion to numerical values. This study presents an innovative framework by integrating financial ratios, commonly used in company evaluation methodologies, with FAHP, which is capable of processing complex and uncertain data. The integration of financial ratios into FAHP enhances the accuracy and clarity in decision-making processes for evaluating and ranking companies while also allowing for the management of the inherent uncertainties in economic data. Furthermore, SOM, an unsupervised artificial intelligence method for company classification, is used. Net Profit Margin is the financial ratio evaluated with the highest weight among financial ratios by 0.38. After the FAHP phase, financial ratios obtained from the income statements and balance sheets of companies are multiplied by the respective weights for valuation. In the final phase, a total of 6 companies listed in the Borsa Istanbul Insurance Index are divided into 3 classes. The two companies receiving the highest valuation, AGESA (Agesa Life and Pension) and ANHYT (Anadolu Life Pension Joint Stock Company), have been classified as Class A. To show the performance of the proposed model, companies registered in the Electricity Sector XELKT registered 31 companies. Classification also performed well in that set. The paper contributes to the field by providing a detailed literature review, methodology, case study results, and discussions on the practical implications of this integrated assessment method and possible areas for further research and applications.

Keywords

Financial Analysis , Multi-Criteria Decision Making , Fuzzy Analytic Hierarchy Process , Machine Learning , Self-Organizing Maps

References

  1. Abusaeed, S., Khan, S. U. R., & Mashkoor, A. (2023). A Fuzzy AHP-based approach for prioritization of cost overhead factors in agile software development. Applied Soft Computing, 133, 109977. https://doi.org/10.1016/j.asoc.2022.109977
  2. Adenso-Díaz, B., Álvarez, N. G., & Alba, J. A. L. (2020). A fuzzy AHP classification of container terminals. Maritime Economics and Logistics, 22(2), 218–238. https://doi.org/10.1057/s41278-019-00144-4
  3. Aldalou, E., & Perçin, S. (2018). Financial Performance Evaluation of Turkish Airline Companies Using Integrated Fuzzy Ahp Fuzzy Topsis Model*. Uluslararası İktisadi ve İdari İncelemeler Dergisi. https://doi.org/10.18092/ulikidince.347925
  4. Basílio, M. P., Pereira, V., Costa, H. G., Santos, M., & Ghosh, A. (2022). A Systematic Review of the Applications of Multi-Criteria Decision Aid Methods (1977–2022). In Electronics (Switzerland) (Vol. 11, Issue 11). MDPI. https://doi.org/10.3390/electronics11111720
  5. Başaran, Y., Aladağ, H., & Işık, Z. (2023). Pythagorean Fuzzy AHP Based Dynamic Subcontractor Management Framework. Buildings, 13(5), 1351. https://doi.org/10.3390/buildings13051351 Beaver, W. (1966). Financial Ratios As Predictors Of Failure. https://doi.org/10.2307/2490171
  6. Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233–247.
  7. Burova, A., Penikas, H., & Popova, S. (2021). Probability of Default Model to Estimate Ex Ante Credit Risk. Russian Journal of Money and Finance. https://doi.org/10.31477/RJMF.202103.49
  8. Çolakoğlu, N., & Şahi̇n, Z. (2022). Determining of Priorities in ERP Project Management with AHP Approach. Eurasian Academy of SciencesEurasian Business & Economics Journal 30, 39-63
  9. Demircan, B. G., & Yetilmezsoy, K. (2023). A Hybrid Fuzzy AHP-TOPSIS Approach for Implementation of Smart Sustainable Waste Management Strategies. Sustainability, 15(8), 6526. https://doi.org/10.3390/su15086526
  10. Duyck, C., da Silva Viana Jacobson, L., Rodrigues de Souza, J., Chavez Rocha, R. C., Oliveira, C. J. F., Oliveira da Fonseca, T. C., & Saint’Pierre, T. D. (2023). Brazilian basins characterization based on the distributions of elements in desalted crude oils using classical multivariate analysis and kohonen self-organizing map. Geoenergy Science and Engineering, 223. https://doi.org/10.1016/j.geoen.2023.211502
APA
Yiğit, F. (2024). Hybrid Approach for the Financial Assessment of Companies using Fuzzy Multi-Criteria Decision-Making and Self-Organizing Maps. İnsan Ve Toplum Bilimleri Araştırmaları Dergisi, 13(2), 610-629. https://doi.org/10.15869/itobiad.1404060