Determinants of Non- Performing Loans Among Commercial Banks in Tanzania

Abstract

Commercial Banks (CBs) are the most significant contributors to a nation's financial sector, and their primary objective is to preserve economic stability and long-term growth. These banks are the main players in the banking sector and funding sources for business activities and other projects. They adopt the basic rule of receiving money from savers in the name of deposits and then disburse them to the customers in the name of advances or loans. However, these banks are held back when their primary sources of income, namely loans and advances, stop performing. High levels of Non-Performing Loans (NPLs) in CBs have a detrimental impact on private investment, which make it more difficult for banks to pay their debts as they become due, and limit the amount of credit available to borrowers. NPLs are thought to be significantly influenced by both internal and external economic situations. The primary objective of this study was to determine the extent to which bank-specific factors; board composition; macroeconomic factors; and monetary policy indicators affect the frequency of NPLs in commercial banks of Tanzania by assessing the relationship between NPLs and these variables. The study employed a quantitative research design to examine the drivers of NPLs in a sample of 31 commercial banks (CBs) in Tanzania over the 10-year period from 2011 to 2020. The researcher employed balanced panel data sourced from the Bank of Tanzania (BoT), the National Bureau of Statistics (NBS), and the audited financial reports of the selected CBs. Utilising balanced panel data enabled a thorough analysis of the CBs over a complete 10-year period, offering a more robust and comprehensive dataset for investigating the determinants of NPLs. The combination of regulatory data from the Central Bank, National Bureau of Statistics, and audited financial information from the CBs themselves strengthens the reliability and validity of the data used in the analysis. Data were analysed descriptively and inferentially using Stata, while a generalised method of moments (GMM) regression model was carried out to investigate the drivers of NPLs. Results for the first objective demonstrated that return on assets (ROA) and income diversification (INC-DIV) of CBs have a negative impact on the amount of NPLs. The reciprocal nature of these relationships implies a two-way causal effect between the variables. Higher ROA and INC-DIV not only drive lower NPLs, but the reduced NPL levels, in turn, enable banks to maintain stronger profitability and more diversified income sources. This type of reciprocal relationship highlights the complex and interdependent dynamics at play within the commercial banking sector when it comes to managing NPLs. The findings suggest that interventions targeting either ROA improvement or INC-DIV could have a mutually reinforcing impact on reducing NPLs in Tanzanian commercial banks. Theoretically, these results suggest that banks should retain profitability and expand rather than contract their debtor credit supply in order to reduce loan defaults that could harm banks' asset quality. On the second objective, it was found that the number of board members with financial expert (FEXP); the board size (BZE); the audit committee (AC); and the presence of female directors (FD) influence the number of NPLs negatively. Moreover, the Agency Theory posits that boards with at most eight members operate more effectively and aid in lowering the number of NPLs. In contrast, a large number of BZE; board credit committees (CC); and independent directors (IND-DIR) increase the number of NPLs. These results show that banks should maintain efficient corporate governance processes to monitor financing activities and decrease NPLs in order to cut loan defaults that could worsen banks' asset quality. Results for the third objective showed that macroeconomic factors, irrespective of bank size and ownership categories, favour and strongly impact NPLs. The findings indicate a strong correlation between Gross Domestic Product (GDP) and NPLs. Key predictors of expected declines in NPLs include increased foreign direct investment (FDI), reduced unemployment (UNEMP), and lower inflation rates (INF). The fourth objective of the study revealed a significant positive effect of monetary policy dynamics on the percentage growth of NPLs. These findings indicate that changes in monetary policy influence the lending decisions of CBs and the cash flows of borrowers, ultimately reducing the debt repayment capacity of bank customers. The study recommends the need for commercial banks to actively track monetary policy developments and manage the trade-offs between their key objectives (such as profitability) in order to effectively serve the real economy. Additionally, credit assessment procedures should be taken into account in business policy changes in order to raise the caliber of bank loan portfolios. To reduce loan default rates, small and foreign banks should rigorously vet their borrowers. In order to slow the rate of defaulters, management must also make some strategic choices such as strengthening credit underwriting practices, diversifying loan portfolios, improving loan monitoring and early warning systems, enhancing collections and workout strategies, and fostering relationships and client engagement. Furthermore, the decision-makers should establish a stable monetary policy which would, in turn, serve to slow the expansion of NPLs, maximise profits, strengthen banks' ability to act as financial intermediaries, and ultimately accelerate economic growth in the country. Moreover, regulators must enforce reserve requirements (RRs) and capital adequacy (CAR) regulation for the purpose of controlling excessive risk-taking behaviour in thinly capitalised banks. Furthermore, the Bank of Tanzania should implement prudential lending practices to mitigate NPLs during periods of high lending activity. Again, credit bureau facilities should be availed to smaller banks to track down multiple borrowers. Furthermore, government authorities should conduct regular stress tests on banks to assess their capacity to withstand macroeconomic shocks and changes in monetary policy. The results of this study will contribute to several theories in various ways. For example, taking into account asymmetric information theory, the study showed that a bank may reduce the default risk posed by adverse selection and moral hazard issues provided it obtains accurate information from borrowers. Adverse selection and moral hazards have caused a significant buildup of NPLs. For the agency theory (AT), the study will contribute to small boards by reducing NPLs and efficiently monitor and bring about profits, especially in an emerging economy context. Furthermore, diverse boards are needed in emerging economies because of the weak institutions that need various complementary skills. Additionally, the study made a contribution to financial theory by showing how any shift in macroeconomic and monetary policy variables confuses players like CBs and decreases borrowers' likelihood of being able to repay their debts, which causes NPLs to accumulate. By incorporating financial theory, researchers can gain a more comprehensive understanding of how macroeconomic factors and monetary policy indicators influence the landscape of NPLs in the commercial banking sector. This theoretical foundation can guide the empirical analysis and help identify the channels through which these external factors influence NPL dynamic