Assessing the severity of non-performing loans for residential and non-residential properties in Malaysia - Sing, Ramila Devi Ram; Hosin, Husnizam; Mohamad, Shafi; Bawazir, Abdullah Abdulaziz (Journal of Asian Scientific Research, 2024)
This study attempts to assess the macroeconomic factors impacting non-performing loans (NPLs) in both residential and non-residential properties held by commercial and Islamic banks in Malaysia between 2007 and 2021. The study will analyze quarterly NPL (non-performing loan) ratio data from reputable sources like Bank Negara, International Financial Statistics, and the Bank for International Settlements. It will focus on NPL trends across different property types in commercial and Islamic banks. Using the Autoregressive Distributed Lag (ARDL) technique, the study will evaluate the long-term relationship between NPLs and key macroeconomic factors. The results show a proven cointegrating link between determinants and NPLs. This provides crucial insights into fostering economic growth through macroeconomic factors while also bolstering the overall sustainability of the financial systems. The models are designed to anticipate non-performing loans based on data from Q12007- Q22021. Thus, the conclusions have practical limits, such as distortions in reflecting actual conditions or trends. Since then, the economy, society, and technology have all changed dramatically. Furthermore, human behaviors and preferences might change, making previous patterns less dependable for forecasting future actions. Key regulatory authorities, such as Bank Negara Malaysia, have developed measures to detect and address imbalances and vulnerabilities in the financial industry. Many of these measures have long lags; thus, it is important to identify macroeconomic and macro-financial factors that could act as leading indicators for future non-performing loan developments. The paper primarily contributes by estimating models to predict variables related to non-performing loans (NPLs). Its findings are valuable to regulatory agencies, as these agencies often rely on delayed indicators to identify key drivers of NPLs, including macroeconomic and bank-specific factors.