Because the nature of municipalities differs from that of commercial institutions, norms and standards for the determination of creditworthiness are also different. Although various documented models and studies addressing credit rating related issues in the commercial sector are available, no objective model for determining the creditworthiness of municipalities has been published in South Africa. This model has been developed specifically for the determination of the creditworthiness of municipalities and is based on objective standards. All the indicators applied in the model are calculated objectively. The net product of the model is therefore a numerical figure indicating creditworthiness at a specific time. The model shows the numerical composition of the figure, and specific indicators or norms of interest can be studied in greater detail. The model has the following unique features: • It calculates a numerical value, representing the creditworthiness of a municipality. • The determination of the creditworthiness figure is objective. • Trends are calculated and form part of the calculation of the creditworthiness figure. • The model is parameter-driven - by merely changing the values in the parameter file, all the calculations are changed accordingly. • The creditworthiness figure from the model does not claim to be an absolutely accurate representation of the creditworthiness of a municipality, but claims to be accurate enough (80/20 principle) to form a basis for reliable and effective management decisions. This model is the first in South Africa. to offer a means of determining the creditworthiness of municipalities objectively. It is a simple model which is based on the elements representing creditworthiness. / Accounting / D. Comm. (Accounting)

Because the nature of municipalities differs from that of commercial institutions, norms and standards for the determination of creditworthiness are also different. Although various documented models and studies addressing credit rating related issues in the commercial sector are available, no objective model for determining the creditworthiness of municipalities has been published in South Africa. This model has been developed specifically for the determination of the creditworthiness of municipalities and is based on objective standards. All the indicators applied in the model are calculated objectively. The net product of the model is therefore a numerical figure indicating creditworthiness at a specific time. The model shows the numerical composition of the figure, and specific indicators or norms of interest can be studied in greater detail. The model has the following unique features: • It calculates a numerical value, representing the creditworthiness of a municipality. • The determination of the creditworthiness figure is objective. • Trends are calculated and form part of the calculation of the creditworthiness figure. • The model is parameter-driven - by merely changing the values in the parameter file, all the calculations are changed accordingly. • The creditworthiness figure from the model does not claim to be an absolutely accurate representation of the creditworthiness of a municipality, but claims to be accurate enough (80/20 principle) to form a basis for reliable and effective management decisions. This model is the first in South Africa. to offer a means of determining the creditworthiness of municipalities objectively. It is a simple model which is based on the elements representing creditworthiness. / Accounting / D. Comm. (Accounting)

This study examined the determinants of commercial bank liquidity in South Africa. The panel regression approach was used, applying panel data from twelve commercial banks over the period 2006 to 2016. A quantitative research method was used to investigate the relationship between bank liquidity and some microeconomic and bank-specific factors and between bank liquidity and selected macro-economic factors. The regression analysis for four liquidity ratios was conducted using the pooled ordinary least squares regression, fixed effects, random effects and the generalised methods of moments. However, the system generalised methods of moments approach was preferred over the other methods because it eliminated the problem of endogeneity. Results show that capital adequacy, size and gross domestic product have a positive and significant effect on liquidity. Loan growth and non-performing loans had a negative and significant effect on liquidity. Inflation had both a positive and a negative but an insignificant effect on liquidity. The study concluded that South African banks could enhance their liquidity positions by tightening their loan-underwriting criteria and credit policies. Banks should improve their credit risk management frameworks to be more prudent in their lending practices to improve the quality of the loan book to enhance liquidity. They also need to grow their capital levels by embarking on efficient revenue enhancements activities. Banks may also to look at their clients on an overall basis and not on transaction bases, and they need to improve non-interest revenue by introducing innovated products. The South African Reserve Bank could push for policies that might enhance capitalisation by ensuring that the sector is consolidated and thus merging smaller banks to create banks with stronger balance sheets and stronger capital base. This study contributes to the empirical research repository on the determinants of liquidity and more specifically, it identified the significant factors that affect South African commercial bank liquidity. Identifying the determinants of South African commercial bank liquidity will provide the South African Reserve Bank with insight into ways of enhancing liquidity management reforms, to improve the sector’s liquidity management practices and help to maintain a sound and liquid banking sector. / Business Management / M. Com. (Business Management)

The objective of this research is to investigate the existence of structural changes in unsecured lending time series data and analyse the impact thereof on trends in consumer demand for unsecured credit spanning the years from 2008 to 2015. This is achieved by identifying dates when structural changes occurred over this period. The identified structural break date is linked to an influential economic event or monetary policy change that took place in South Africa of which the impact on three unsecured credit categories are analysed. Unsecured credit growth in South Africa has been subjected to intensive scrutiny since the inception of the National Credit Act (Act No. 34 of 2005) by various regulatory bodies. In 2012 the National Credit Regulator (NCR) commissioned a research study into examining the impact that the National Credit Act (Act No. 34 of 2005) has had on the consumer credit market. The empirical part of this study involved the gathering of time series data on unsecured loans approved, unsecured credit granted per income category and unsecured credit granted from the National Credit Regulator (NCR) database and performing descriptive and econometric analysis. The Zivot-Andrews (1992) and augmented Dickey-Fuller tests determined the break dates which were linked to a significant economic event while the one sample t-test of means compared average loan values before and after the break date. Results of the study indicate that the break dates determined coincided with economic events and monetary policy changes in South Africa, such as the collapse of African Bank, the implementation of the National Credit Amendment Act, prime interest rate movements and the introduction of a debt counselling program by the government. These events, coupled with stricter lending criteria and no further loans being granted to customers already more than three months in arrears, restrained the uptake of unsecured loans to lower and middle income groups. The introduction of new affordability criteria and increasing interest rates in 2014 further negatively impacted demand for unsecured loans. However, higher income earners had the advantage of being able to apply for higher loan amounts. Findings could be used by monetary policymakers and financial institutions to constantly monitor credit trends, improve credit assessment techniques and review lending criteria. / Business Management / M. Com. (Financial Management)