أثر احتساب الخسائر الائتمانية المتوقعة وفقا لمعيار التقارير المالية الدولي (9 IFRS)‎ في جودة المستحقات : دراسة تحليلية على المصارف التقليدية المدرجة في سوق دمشق للأوراق المالية

الملخص EN

This paper investigates the impact of calculating expected credit losses in accordance with IFRS (9) on the quality of accruals regarding the conventional banks listed on the Damascus securities exchange, based on the published financial statements for the year ended December 31, 2019, which include the restated financial statements for the years 2018 and 2017 in accordance with IFRS (9) in addition to the 2019 financial statements.

The expected credit losses represented the independent variable.

It was measured using data from the income statements and notes of banks.

The quality of accruals represented the dependent variable.

It was measured by the discretionary accruals which is equal to total accruals minus the non-discretionary accruals by using data from financial position, income statements and cash flow statements of banks.

The size of the bank was relied on as a control variable and it was measured by the natural logarithm of the bank’s total assets.

The descriptive and analytical approach followed in this paper using a sample of (11) banks representing the conventional banks listed on the Damascus securities exchange during the period 2017, 2018 and 2019, using panel data to test the paper hypothesis.

The paper concluded that: There is a significant positive impact for the calculation of expected credit losses in accordance with IFRS (9) on the quality of accruals according to the size of the total assets which helped to recognize credit losses in a timely manner without delaying recognition of credit losses until they occurred.

There is a significant positive impact for the size of the total assets on the quality of accruals.

That means banks with large total assets had higher quality financial data, which may be explained by those banks using more advanced technologies when performing the credit classification of credit facilities to calculate expected credit loss.