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DOI :10.26650/B/SS10.2023.001.10   IUP :10.26650/B/SS10.2023.001.10    Full Text (PDF)

Predicting the Probability of Default with the Help of Macroeconomic Indicators in IFRS 9 Provision Calculations

Muhammed Işık, Bahar Sennaroğlu, Mine Genç

IFRS 9 process has a significant issue for banks. IFRS 9 process assists banks in calculating and managing their mandatory provision. The probability of Default is one of the essential parameters in the IFRS 9 process. This process has two different Probabilities of Default (Through-The-Cycle and Point-In-Time). However, Point-In-Time Probability of Default, where only macroeconomic effects are reflected, is used in the required provision calculation. Through-The-Cycle Probability of Default cannot be used directly for provision calculation. Point-In-Time Probability of Default will be obtained by reflecting macroeconomic effects. In this study, it has been provided to convert Through-The-Cycle Probability of Default to Point-In-Time Probability of Default. Relief Approach and Genetic Algorithm (Evolutionary Search) were used in the feature selection stage. k–Nearest Neighbors, MultiLayer Perceptron, and Extreme Gradient Boosting were used during the creation of the model. In this study, contemporary feature selection and modeling techniques were applied to the data set, and the results were compared. In this study, contemporary regression models used seem to be quite successful.


Keywords: Macroeconomic Modeling, Through-The-Cycle Probability of Default, Point-In-Time Probability of Default, Feature Selection, Regression Models, Modeling Success

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