WHAT CAN BE EXPECTED IN CREDIT-RISK MANAGEMENT FROM NPL IN THE WESTERN BALKANS REGION IN THE FUTURE2?

This paper presents an analysis of the impact of the rate of selected parameters on the banking systemperformance, specifically to non-performing loans (NPLs) movements. The goal is to investigate which themost influential factors affecting the movement of NPLs in the WB countries are, given that research havepointed out the impact of macroeconomic factors on the formation of NPL rates in banking systems. Theauthors have added several parameters to their methodology, dividing the indicators into internal andexternal. On the topic of indicators that affect the performance of the banking system, but also predictionsof future trends of NPLs, several hypotheses can be set, but this research will start from the hypothesis thatthe NPL trend can be predicted by creating predictive models which, as the basis, have a combination ofmacroeconomic and banking system performance indicators. In addition to scientific literature,publications of international development and those by financial institutions were used as well, and theauthors also accessed the international database – CEIC data. The time aspect of the research will coverthe period 2010-2019, and the prediction of NPL trends will be performed for the period 2020-2025. Todetermine the final model and the indicator that will most accurately describe the target variable, theMerton’s model in the statistical tool R will be developed and prediction tests will be fey performed. Themost important statistical methods: linear regression, R2, ADJ R2, correlation matrix. The results showthat in 3 out of 5 observed indicators, the one that most influences the trend of problem loans is theunemployment rate. Based on the modelling, the outputs indicate small deviations between the NPLobtained by the model and the publicly announced NPL-trends are very well presented, and the forecastresults indicate a sharpening of the NPL trend curve in the period up to 2025. The contribution of this paper is reflected in the time prediction of NPL trends which can be useful to state authorities for adequatemeasure implementation.