EFFECTS OF PROVISION FOR EXPECTED CREDIT LOSSES UNDER IFRS 9 ON THE QUALITY OF RESULTS AND CAPITAL STRUCTURE OF BRAZILIAN FINANCIAL INSTITUTIONS

Abstract

Until 2017, CPC 38 (Financial Instruments: Recognition and Measurement), equivalent to IAS 39, was applied in Brazil, which applied the impairment of financial assets through objective evidence of impairment. However, due to its inability to promptly reflect the economic risk associated with the credit operations of financial institutions, starting in 2018, IFRS 9 (CPC 48) was adopted, introducing the expected credit loss (ECL) model, changing the recognition, measurement, and timing of provisions for losses on financial instruments. In the banking sector, this change had a direct impact on the accounting results and capital structure of these institutions. This study aims to analyze the effects of the provision for expected credit losses, resulting from the adoption of IFRS 9, on indicators of the quality of results and capital structure of Brazilian financial institutions. The research uses secondary data extracted from IFData/Central Bank of Brazil, for the period from 2014 to 2024, covering the periods before and after the adoption of IFRS 9. Methodologically, descriptive statistics, mean difference tests, and a linear regression model were applied to assess the association between ECL provisions, earnings quality, and capital structure. The results indicated that, in the post-IFRS 9 period, Brazilian financial institutions showed an increase in provisions for expected credit losses and net income, with no statistically significant changes in the provision/credit ratio, return on assets, and capital structure indicators, suggesting more economic than statistical impacts on the quality of results and solvency. In this context, the main contribution of this study lies in the use of a comprehensive and standardized regulatory database, IFData from the Central Bank of Brazil, covering the period from 2014 to 2024 and allowing for a comparison, within the same analytical framework, of the pre- and post-adoption stages of IFRS 9. From a methodological point of view, the study integrates indicators of accounting results quality (LLP, LLP Ratio, Profit, ROA, and profit volatility) and capital structure (Capital, Net Equity, Total Assets, and PA Ratio) in statistical models that explore the association with the provision for expected credit losses under IFRS 9. This joint approach contributes to the advancement of the national literature by offering recent empirical evidence on the effects of the standard on the largest classified credit portfolios of banking conglomerates, using quantitative tools typical of empirical-analytical research in accounting and finance.