Manya Orellana, Marlon VicenteGonzález Rabanal, Miryam de la Concepción2024-05-202024-05-202023-04-302714-9838; eISSN 2714-9838https://doi.org/10.52728/ijtc.v4i2.723https://hdl.handle.net/20.500.14468/11858The pandemic has caused many businesses to experience a significant decline in revenue and profitability, leading to a decrease in the value of their assets. As a result, companies may need to assess whether their assets have been impaired and take an impairment charge if necessary. This caused companies in general to modify the accounting treatment under the international standard IFRS 9 applicable from 2018. The objective of this article is to determine the portfolio risk that affects the calculation of these provisions, through a case study in Ecuador. The research approach used was mixed (qualitative and quantitative), since various types of data collection tools were used to process the information. The data treatment in the qualitative approach consists of the analysis of the phenomenon related to the exploration for the understanding of the IFRS 9 accounting standard. On the other hand, the quantitative approach intends to analyze the research variables and measure them numerically with the use of statistical methods using Binary Logistic Regression. To this end, a database of clients of a non-financial company was analyzed, and the composition of its portfolio segmented by day of delay, observing the component called probability of default (PD), which was determined by binary logistic regression. A model was obtained that allowed to obtain the desired probability, and consequently under the approach of IFRS 9, the calculation of the expected credit loss (ECL). The results obtained estimated a portfolio impairment of 23%, compared to the baseline scenario of 9%.enAtribución 4.0 Internacionalinfo:eu-repo/semantics/openAccessartículoIFRS 9ImpairmentDefaultCreditRegression