<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Non-Performing Loans (NPLs) are representing nowadays one of the main challenges for the banking systems all over the world. Therefore, a sustainable decision-making process should be implemented, for minimizing the effects of credit risk. The current paper uses a dynamic panel regression model to present the determinants of NPLs for the largest five banks of the Romanian Banking System during 2007-2016. A Generalized Method of Moments (GMM) regression is used and defined under three different types of variables: bank specific indicators, macroeconomic indicators and qualitative variables. Other studies illustrated also the determinants of NPLs in various banking systems from all around the world, such as Japan, China or several CEE countries (especially the emergent ones). After an in-depth analysis of the literature and Romanian market, the following variables were found to be relevant and were introduced into a dynamic data panel model: unemployment rate, annual average growth rate of gross domestic product, return on equity (ROE), loan to deposit ratio (LTD). The existing literature presents ROE as having a negative impact on NPLs, unemployment rate being positive correlated with NPLs and a negative relationship between economic growth and such loans. Our contribution to the current literature is represented by the introduction of two additional qualitative variables (Board Risk Management Ratio (BRMR), as the proportion of risk managers within the Board of Directors of each bank in question and the Expert Aggregate Priority Vector (EAPV), as the aggregated perceived risk regarding the NPLs). The decision of introducing these variables relies on previous research made in this area, results being validated by experts from the Romanian Banking System, according to the BASEL III and NBR criteria. The results of the current paper are consistent with the existent literature, the correlations and impact of the variables being relevant for the subject matter.</p></abstract>

Non-Performing Loans (NPLs) are representing nowadays one of the main challenges for the banking systems all over the world. Therefore, a sustainable decision-making process should be implemented, for minimizing the effects of credit risk. The current paper uses a dynamic panel regression model to present the determinants of NPLs for the largest five banks of the Romanian Banking System during 2007-2016. A Generalized Method of Moments (GMM) regression is used and defined under three different types of variables: bank specific indicators, macroeconomic indicators and qualitative variables. Other studies illustrated also the determinants of NPLs in various banking systems from all around the world, such as Japan, China or several CEE countries (especially the emergent ones). After an in-depth analysis of the literature and Romanian market, the following variables were found to be relevant and were introduced into a dynamic data panel model: unemployment rate, annual average growth rate of gross domestic product, return on equity (ROE), loan to deposit ratio (LTD). The existing literature presents ROE as having a negative impact on NPLs, unemployment rate being positive correlated with NPLs and a negative relationship between economic growth and such loans. Our contribution to the current literature is represented by the introduction of two additional qualitative variables (Board Risk Management Ratio (BRMR), as the proportion of risk managers within the Board of Directors of each bank in question and the Expert Aggregate Priority Vector (EAPV), as the aggregated perceived risk regarding the NPLs). The decision of introducing these variables relies on previous research made in this area, results being validated by experts from the Romanian Banking System, according to the BASEL III and NBR criteria. The results of the current paper are consistent with the existent literature, the correlations and impact of the variables being relevant for the subject matter.

Non-performing loans decision making in the Romanian banking system

The Bucharest University of Economic Studies – ASE

Management & Marketing

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Non-performing loans decision making in the Romanian banking system"}

Non-Performing Loans (NPLs) are representing nowadays one of the main challenges for the banking systems all over the world. Therefore, a sustainable...

Non-performing loans decision making in the Romanian banking system

Data publikacji: 20 mar 2018

Zakres stron: 761 - 776

DOI: https://doi.org/10.2478/mmcks-2018-0004

Słowa kluczowe
Non-performing loans, decisional processes, banking performance, risk evaluation, Analytic Hierarchy Process (AHP), Generalized Method of Moments, dynamic panel data model

© 2018 Ionuț-Daniel Pop et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Non-performing loans decision making in the Romanian banking system

Data publikacji: 20 mar 2018

Zakres stron: 761 - 776

DOI: https://doi.org/10.2478/mmcks-2018-0004

Słowa kluczoweNon-performing loans, decisional processes, banking performance, risk evaluation, Analytic Hierarchy Process (AHP), Generalized Method of Moments, dynamic panel data model

© 2018 Ionuț-Daniel Pop et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
Non-performing loans, decisional processes, banking performance, risk evaluation, Analytic Hierarchy Process (AHP), Generalized Method of Moments, dynamic panel data model