Search results

This paper explores the possibilities for policy coordination in the Southern African Development Community (SADC) as well as real effective exchange rate (REER) stability as a prerequisite towards sensible monetary integration. The underlying hypothesis goes with the assertion that countries meeting optimum currency area conditions face more stable exchange rates.

The quantitative analysis encompasses 12 SADC member states over the period 1995-2012. Correlation matrixes, dynamic pooled mean group (PMG) and mean group (MG) estimators and real effective exchange rate (REER) and real exchange rate (RER) equilibrium and misalignment analysis are carried out to arrive at the conclusions.

The study finds that the structural variables used in the PMG model show that there are common fiscal and monetary policy variables that determine REER/RER in the region. However, the exchange rate equilibrium misalignment analysis reveals that SADC economies are characterised by persistent overvaluation at least in the short term. This calls for further sustained policy coordination in the region.

The findings in this paper have important policy implications for economic stability and for the attempt of policy coordination in SADC region for the proposed monetary integration to proceed.

This study is the first attempt that relates the exchange rate as a policy coordination instrument among SADC economies.

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.

The purpose of this study is to examine the level of effectiveness of the anti-fraud technologies employed by the South African banking industry for cyberfraud mitigation.

This research employed a qualitative research design involving a purposive sampling method. Primary data was collected from the key organisational staff across the 17 licensed commercial banks in South Africa via the use of structured questionnaires. In particular, these were experts involved in combating fraud and taking managerial decisions regarding the use of anti-fraud technologies for cyberfraud mitigation. Non-parametric statistical analyses were carried out from the responses obtained.

The results obtained indicated that the combination of internal and external anti-fraud technologies such as filtering software, firewalls, encryption, continuous auditing, discovery sampling, virus protection, financial ratios, digital analysis and data mining may have a positive effect on cyberfraud mitigation. These technologies are employed mostly to ensure effective internal control systems capable of minimising cyberfraud. In addition, the anti-fraud technologies employed in the South African banking industry may also be effective in the mitigation of cyberfraud, although significant cases of cyberattacks were reported by the respondents.

The study recommends investment in more digital and emerging technologies and the development of human capacities to effectively deploy them in the combat against cybercrime.

The novelty of this study lies in the identification of the type of anti-fraud technologies/software employed by the South African banking industry and their level of effectiveness or success rate.

The purpose of this paper is to review the effect of cybercrime in the banking sector.

This study uses a survey of literature and the balanced scorecard (BSC) to analyse the effect of cybercrime on the banking sector.

The literature reviewed confirms an increasing wave of cybercrime that has impacted negatively on the good will and economic growth of financial institutions, indirectly through loss of trust in the digital infrastructure or directly through fraud and extortion in both developing and developed countries.

This study is limited to the application of BSC to analyse the effect of cybercrime in the banking sector only.

To avert on going massive losses owing to cybercrime, the authors quest for development of an alert system that can create the awareness of both the banks and the customers by effectively implementing and integrating big data technology into their system to mitigate the negative impacts of cybercrime.

The novelty of this study lies in the fact that this study uses the BSC for the analysis of cybercrime in the banking sector, a problem that has not been sufficiently highlighted in the existing literature.

The purpose of this study is to use a decision support model based on the Analytical Hierarchy Process (AHP) and Pareto analysis (PA) for ranking the impact of different kinds of cybercrime in organisations in the financial sector to support decisions on cybercrime mitigation.

From a structured questionnaire to the staff of 17 licensed banks in South Africa in charge of management, administration and operations, the perceived effect of cybercrime on the organisation’s goals, namely, organisation’s profitability, goodwill, customers’ satisfaction and risk management was derived. The pairwise comparison of the organisation’s goals and identified forms of cybercrime was done using the AHP.

The results obtained indicate that there was a consensus (100% of the answers) that the effect of cybercrime has negatively impacted the organisation’s objectives profitability and goodwill. Also, still 95.23% of the respondents agreed that the effect of cybercrime has negatively impacted the level of customers’ satisfaction, while only 7.15% saw an impact on the organisation’s risk management processes. Using these results in the AHP, analysis delivers a hierarchical order about the relevance of prevalent forms of cybercrime for the organisation´s cybercrime mitigation. The PA further shows the magnitude of the forms of cybercrime relative to each other.

Hence, this study provides a decision support framework for organisational management in the quest to explore the impact of cyber fraud. It can serve as a practical guided approach for the application of AHP analysis for the existing and emerging forms of cybercrime.

The novelty of this study lies in the fact that the combination of the AHP and PA to support solving a multi-criteria decision problem relating to the prevalence of cybercrime has not been sufficiently highlighted by the existing literature.

The purpose of this study is to assess the impact of cyberfraud in the South African banks with the aim to provide recommendations to effectively mitigate it.

The study uses a qualitative approach involving the use of structured questionnaires. The questionnaires were made available to the staff of 17 licensed banks in South Africa who deal with management, operation, administration and banking services. Two hypotheses were formulated and non-parametric statistical analyses involving the use of Chi-square test, Fischer’s Exact test and Spearman’s correlation were carried out. The two hypotheses formulated were tested to draw a conclusion.

The results obtained indicate that the impact of cyberfraud in the South African banking industry is highly significant and has affected the reputation of some of the banks. This calls for the need to review the diverse ways of curbing cyberfraud to lessen their impact and that of associated fraud risks on the banking operation.

This study provides an analysis on the relationship cyberfraud occurrences and the reputation of South African banks. The implementation of the recommendations may reinforce the existing security measures in the fight against cyberfraud.

The novelty of this study lies in the fact that the assessment of the impact of cyberfraud on the banking industry in South Africa has not been sufficiently highlighted by the existing literature.

This study aims to investigate the feasibility of employing a multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation. The formulated objectives are the minimisation of the total allocation cost of the anti-fraud capacities and the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots.

From the literature survey conducted and primary qualitative data gathered from the 17 licenced banks in South Africa on fraud investigators, the suggested fraud investigators are the organisation’s finance department, the internal audit committee, the external risk manager, accountants and forensic accountants. These five human resource capacities were considered for the formulation of the multi-objectives integer programming (MOIP) model. The MOIP model is employed for the optimisation of the employed capacities for cyberfraud mitigation to ensure the effective allocation and utilisation of human resources. Thus, the MOIP model is validated by a genetic algorithm (GA) solver to obtain the Pareto-optimum solution without the violation of the identified constraints.

The formulated objective functions are optimised simultaneously. The Pareto front for the two objectives of the MOIP model comprises the set of optimal solutions, which are not dominated by any other feasible solution. These are the feasible choices, which indicate the suitability of the MOIP to achieve the set objectives.

The results obtained indicate the feasibility of simultaneously achieving the minimisation of the total allocation cost of the anti-fraud capacities, or the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots – or the trade-off between them, if they cannot be reached simultaneously. This study recommends the use of an iterative MOIP framework for decision-makers which may aid decision-making with respect to the allocation and utilisation of human resources.

The originality of this work lies in the development of multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation.