Evaluating the Credit Risk and Macroeconomic Interaction in South African Banks: Array - Khumalo, Siyabonga; Ferreira-Schenk, Suné; Van Rensburg , Johnny Jansen; Mokatsanyane, Danny (Acta Universitatis Danubius. Œconomica, 2021)
Banks are the backbone of a country’s financial system, and they play an essential role in providing liquidity in the market economy. However, in doing so, they experience a great challenge of credit risk, which is primarily influenced by macroeconomic factors that directly affect borrowers’ behaviour. This study examined the co-integrating relationship between credit risk and macroeconomic interactions on South African banks in the long-term and short–term. To also provide additional knowledge to the already existing information on factors that drive credit risk for the top 5 South African commercial banks, looking at the influence of macroeconomic factors from 2009 to 2018/19. Previous research has confirmed the relationship between macroeconomic factors and non- performing portfolios or credit risks. Results obtained indicate no significant long-run relationship between market rates (interest rates) and GDP growth rates and a positive relationship between unemployment and money supply. On the other side, the exchange rate and inflation rate share a negative relationship. Thus, this study found a long-run relationship between credit risk and the observed significant macroeconomic variables. Objectives This article will examine the influence of structural factors or macroeconomic interaction on credit risk that affects bank loans portfolio (banks assets) /profitability in the South African context. Prior Work Previous scholars focused on data before the financial crisis using mainly stress testing econometric models. However previous studies have left some research questions unanswered. For instance, has the global debt increased and is more than what was in 2008/2009, and is the world economy sleepwalking into a future/next financial crisis? Will there be another global financial crisis? And if so, how will it affect South Africa? Will it emanate from credit risk again? Therefore, the underlying study will identify possible causes or factors of credit risk for the South African banking sector. Approach This study made use of both a literature review and an empirical study, using secondary data. For the empirical analysis, a statistical analysis was carried out using the latest version of Eviews. The study will employ recent aggregate available data on SARB and StatsSA from 2009 – 2018/1 Results The results of this study found that the is a negative relationship between credit risk, ROA and ROE, which shows strong statistical significance on the relationship of the variables. The study then followed a second model which was aimed at finding long-run relations between credit risk and macroeconomic factors. A negative relationship was then found on the Inflation rate, Exchange rate and GDP growth rate, whereas a positive relationship was established between the Unemployment rate, Market/leading rate, and Money supply. However, for the GDP growth rate and the Market/lending rate, the results confirmed an insignificant relationship, meaning that the is no significant long-run relationship between these two macroeconomic factors and credit risk. Implications 1 2 Bank managers or the monetary authorities need to effectively supervise or manage the selection and previous of credit to borrowers and create banking models that will account for macroeconomic aspects that may cause future changes in the behaviour of borrowers. In all things considered, this article implies that the South African Reserve Bank, along with financial authorities need to create a guideline that will give rise to the improvement of credit risk control measures and reduce the flow of expanding non-performing loans within the South African banks. Value This study aims to examine the co-integrating relationship between credit risk and macroeconomic interactions on South African banks in the long-term and provide additional knowledge to the already existing information on factors that drive credit risk.