International Istanbul Economic Research Conference (IIERC), İstanbul, Türkiye, 18 - 20 Kasım 2021, ss.77
IFRS
9 process has a very important issue for banks. IFRS 9 process assists banks in
calculating and managing their required provision. Probability of Default is
one of the important parameters in IFRS 9 process. There are two different
Probability of Default (Through-The-Cycle and Point-In Time) in this process.
However, Point-In-Time Probability of Default where only macroeconomic effects
are reflected is used in 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 feature selection
stage. k-Nearest Neighbors, Multi-Layer Perceptron and Extreme Gradient
Boosting were used during creation of 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.