Publication year: 2021
ISBN: Bus00023
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This study aimed to find a model consisting of a set of financial ratios in which each ratio has its own weight that indicate its importance to predict probability of financial loss of conventional and Islamic banks in Syria. The early prediction warns the concerned parties that they can intervene and take corrective actions before the collapses of bank. To achieve this ratios of conventional and Islamic Syrian banks were analyzed using Binary logistic regression from the period of 2011-2020 The statistical results show that the logistic regression model is accurate to predict the probability of a financial loss in conventional banks about 82.2%, 81.3%, 80.1%, 78% before 90 days ,180 days, 270 days, one year respectively. We can generally use five variables (Non-performing debt, return on equity, size, growth rate and financing portfolio ratio) in bank's financial loss prediction, but for Islamic banks, no significant values were shown so we can’t find logistic regression model is accurate for Islamic banks.
Subject: Economics and Finance, Prediction, Financial loss, Conventional banks, Financial ratios, Binary logistic regression