Predictive model based on historical financial indicators to classify risk in ecuadorian segment-one cooperatives
DOI:
https://doi.org/10.62452/ew9ns279Keywords:
Predictive model, financial indicators, financial risk, machine learning, credit unions, Random ForestAbstract
This article presents a supervised classification model based on the Random Forest algorithm to estimate the risk level of segment-one credit unions in Ecuador. Twelve historical financial indicators were analyzed —capital adequacy, asset quality, delinquency, operational efficiency, profitability, liquidity and equity vulnerability— drawn from the annual bulletins of the Superintendence of Popular and Solidarity Economy (SEPS) for the period 2021-2025. The results show that financial intermediation, liquidity, the net capitalization index, return on assets (ROA) and the non-performing loan ratio are the predictors with the highest discriminant power. The multiclass ROC curve confirms robust model performance, with a macro AUC of 0.956 (high: 0.973; low: 0.979; medium: 0.917), exceeding the conventional excellent-discrimination threshold. The findings provide an analytical tool applicable to preventive supervision of Ecuador's popular and solidarity financial system.
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References
Basel Committee on Banking Supervision. (2011). Basel III: A global regulatory framework for more resilient banks and banking systems. Bank for International Settlements. https://www.bis.org/publ/bcbs189.pdf
Basel Committee on Banking Supervision. (2013). Basel III: The liquidity coverage ratio and liquidity risk monitoring tools. Bank for International Settlements. https://www.bis.org/publ/bcbs238.pdf
Bessis, J. (2015). Risk management in banking. John Wiley & Sons.
Damodaran, A. (2014). Applied corporate finance. John Wiley & Sons
Diamond, D. W., & Dybvig, P. H. (1983). Bank runs, deposit insurance, and liquidity. Journal of Political Economy, 91(3), 401–419. https://doi.org/10.1086/261155
Ecuador. Superintendencia de Economía Popular y Solidaria. (2025). Boletines financieros del segmento 1. https://www.seps.gob.ec/boletines/
European Central Bank. (2020). Financial stability review. https://www.ecb.europa.eu/pub/fsr/html/index.en.html
Golin, J., & Delhaise, P. (2013). The bank credit analysis handbook (2nd ed.). Wiley.
Hasan, I., & Wall, L. D. (2004). Determinants of the loan loss allowance: Some cross-country comparisons. Financial Review, 39(1), 129–152. https://doi.org/10.1111/j.0732-8516.2004.00070.x
International Monetary Fund. (2019). The IMF 2019 Financial Soundness Indicators Compilation Guide (2019 FSI Guide). https://www.imf.org/-/media/files/data/2019/2019-fsi-guide.pdf
Ledgerwood, J., & White, V. (2006). Transforming microfinance institutions. World Bank. https://documents1.worldbank.org/curated/en/723801468161668762/pdf/372590Transforming0microfinance.pdf
Mishkin, F. S., & Eakins, S. G. (2017). Financial markets and institutions. Pearson.
Rose, P. S., & Hudgins, S. C. (2013). Bank management & financial services (9th ed.). McGraw-Hill.
Saunders, A., & Cornett, M. M. (2014). Financial institutions management: A risk management approach. McGraw-Hill.
Van Greuning, H., & Bratanovic, S. B. (2020). Analyzing banking risk: A framework for assessing corporate governance and financial risk (5th ed.). World Bank.
World Bank. (2019). Credit scoring approaches guidelines.https://thedocs.worldbank.org/en/doc/935891585869698451-0130022020/original/CREDITSCORINGAPPROACHESGUIDELINESFINALWEB.pdf
World Bank. (2021). Global financial development report 2021. https://openknowledge.worldbank.org/bitstream/handle/10986/35218/211600ovSP.pdf
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