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The study investigates the link between structural transformation and sustainable development in sub-Saharan Africa.

The study adopts the traditional ordinary least square method and the Driscoll and Kraay covariance matrix estimator to address every form of cross-sectional and temporal dependence in panel data.

The study finds the structural transformation of the SSA economy will engender sustainable development. Specifically, the study finds that knowledge exerts a positive and statistically significant impact on sustainable development in SSA. Similarly, we found that technology (mobile cellular subscription and fixed telephone line subscription) promotes sustainable development. The results also show that all the economic transformation promotes sustainable development in SSA. Further, we also found that economic development and physical capital are important drivers of sustainable development in SSA. However, trade openness does not contribute to sustainable development in SSA. This might be because the combined scale effect in trade outweighs the combined technology and composition effects in SSA. This suggests the technology component in total trade activities in SSA does not promote sustainable development. The study recommends that governments across SSA should invest more in ICT and mobile cellular infrastructure or create an enabling environment that encourages digitization and the development of financial technology in the manufacturing, mining, construction, agriculture and services sectors to enhance green and quality growth for sustainable development in SSA.

The study uncovers the role of structural transformation in promoting sustainable development in SSA.

A functional financial sector is a major driver of economic development. The purpose of this paper is to provide a comprehensive understanding of existing research findings, gaps in knowledge and emerging trends in the field of banking and finance.

By conducting a systematic literature review, a total of 98 peer-reviewed articles whose focus and relevance match with the subject matter were reviewed and synthesised to answer the research questions. Multiple regression was also carried to investigate the relationship amongst the identified probable factors affecting financial inclusions.

The outcome of this study highlighted some factors mitigating the growth of the banking sector in the Sub-Saharan Africa (SSA). These include excessive or stringent regulations, market segmentation, high interest rates, information asymmetry, low credit status and uneven distribution of credit amongst others.

Some of the policy recommendations that could aid the development of the banking sector in SSA include: development and deepening of interbank markets, financial inclusion, improvement of overall market efficiency through redistribution of liquidity within the banking system, improvement of price and encouragement of competition. This study recommends financial inclusion by formulating policies that balances the capital adequacy requirements with the risk of insolvency to ensure credit flows and promotes financial stability via effective operations financial institutions.

This study contributes valuable insights to the understanding of banking and financial regulations in SSA, informing both academic research and policy development in the region.

The study examined the effect of fiscal policy on poverty in sub-Saharan Africa (SSA) while accounting asymmetric (captured by economic downturns) and spillover effects.

The study used a fixed effect (within regression) IV model to account for country-specific characteristics. The study also adopts a cross-sectional and spatial dependence-consistent model to account for the potential cross-sectional and temporal dependence in panel data modeling.

The study discovered that the effect of fiscal policy on poverty is dependent on the state of the economy. Specifically, we find that fiscal policy helps to reduce the level of poverty during an economic downturn, more than at any other time. More specifically, the findings indicate that the fiscal policy lowers the rate of poverty in SSA, following macroeconomic shocks (captured by the COVID-19 epidemic, the Global Financial Crisis, and the commodity terms of trade shocks). Our findings suggest that fiscal policy is an important policy tool to mitigate the effects of macroeconomic shocks in SSA. Further, the findings also demonstrate that there is a spillover effect of poverty in the region. This implies coordinated, constructive actions by the regional governments can help to lessen the detrimental effects of extreme poverty.

The study examined the effectiveness of fiscal policy to reduce poverty in the event of an economic downturn.

The purpose of this study is to analyse cyberfraud in the South African banking industry using a multiple regression approach and develop a predictive model for the estimation and prediction of financial losses due to cyberfraud.

To mitigate the occurrence of cyberfraud, this study uses the multiple regression approach to correlate the relationship between financial loss and cyberfraud activities. The cyberfraud activities in South Africa are classified into three, namely, digital banking application, online and mobile banking fraud. Secondary data that captures the rate of cyberfraud occurrences within these three major categories with their resulting financial losses were used for the multiple regression analysis that was carried out in the Statistical Package for Social Science (SPSS, 2022 environment).

The results obtained indicate that the South African financial institutions still incur significant financial losses due to cyberfraud perpetration. The two main independent variables used to estimate the magnitude of financial loss in the South Africa’s banking industry are online (internet) banking fraud (X2) and mobile banking fraud (X3). Furthermore, a multiple regression model equation was developed for the prediction of financial loss as a function of the two independent variables (X2 and X3).

This study adds to the literature on cyberfraud mitigation. The findings may promote the combat against cyberfraud in the South Africa’s financial institutions. It may also assist South Africa’s financial institutions to predict the financial loss that financial institutions can incur over time. It is recommended that South Africa’s financial institutions pay attention to these two key variables and mitigate any associated risks as they are crucial in determining their profitability.

Existing literature indicated significant financial losses to cyberfraud perpetration without establishing any relationship between the magnitude of losses incurred and the prevalent forms of cyberfraud. Thus, the novelty of this study lies in the analysis of cyberfraud in the South African banking industry using a multiple regression approach to link financial losses to the perpetration of the prevalent forms of cyberfraud. It also develops a predictive model for the estimation and projection of financial losses.