Integrated reporting requires a new form of disclosure to provide a holistic view of the organisation and aims to support integrated thinking, decision-making and actions that focus on the creation of value. The International Integrated Reporting <IR> Framework (IIRC 2013b) provides guidelines for the content elements required in an integrated report. One of the content elements is ‘risks and opportunities’. This study firstly assessed whether integrated reporting has enhanced integrated thinking between strategy and the risks and opportunities faced by the organisation. For this purpose, a web-based research questionnaire was sent to high-level implementers of integrated reporting at companies listed on the Johannesburg Stock Exchange (JSE) in South Africa, where integrated reporting is a listing requirement. The results of the study provide new insights for companies preparing integrated reports, as well as other stakeholders, which show that integrated reporting has driven change towards integrated thinking between strategy, risks and opportunities. Secondly, a content analysis was done on a sample derived from the top 100 companies listed on the JSE to determine whether integrated reporting has brought about a change in the disclosure of risks and opportunities. The results provide new research findings and indicate that most companies conform to the disclosure requirements noted in the International <IR> Framework (IIRC 2013b) regarding risks and opportunities except for disclosures relating to the assessment of specific risks. The content analysis further found that integrated reporting has driven limited change in the disclosure of risks and opportunities.

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Standard Bank, South Africa, currently employs a methodology when developing application or behavioural scorecards that involves logistic regression. A key aspect of building logistic regression models entails variable selection which involves dealing with multicollinearity. The objective of this study was to investigate the impact of using different variance inflation factor 1 (VIF) thresholds on the performance of these models in a predictive and discriminatory context and to study the stability of the estimated coefficients in order to advise the bank. The impact of the choice of VIF thresholds was researched by means of an empirical and simulation study. The empirical study involved analysing two large data sets that represent the typical size encountered in a retail credit scoring context. The first analysis concentrated on fitting the various VIF models and comparing the fitted models in terms of the stability of coefficient estimates and goodness-of-fit statistics while the second analysis focused on evaluating the fitted models' predictive ability over time. The simulation study was used to study the effect of multicollinearity in a controlled setting. All the above-mentioned studies indicate that the presence of multicollinearity in large data sets is of much less concern than in small data sets and that the VIF criterion could be relaxed considerably when models are fitted to large data sets. The recommendations in this regard have been accepted and implemented by Standard Bank.

When bank managers are asked to comment on the bank’s performance over the past year, most would quote either their bank’s return on equity or return on assets. If these measures were higher than those of their peers, the bank is referred to as a high‐performance bank. The ratios involved are financial ratios and the main problem with this approach is its reliance on comparable ratios. To find suitable comparable standards (norms) is quite difficult, and when the standard (norm) is not appropriate, the comparison may mislead the analyst. A measurement tool that can compensate for the weaknesses in financial ratios is therefore needed. One such tool that can be used to measure bank performance is Data Envelopment Analysis (DEA). The objective of this article is to draw a comparison between the results of financial ratios (as a conventional performance measurement) and the results obtained by means of DEA with regard to the performance evaluation of the ten regional offices of one of South Africa’s larger banks.

1994 to 2015 on total foreign portfolio investments in liabilities (equity and debt) were collected.Panel data regression analysis incorporating pooled regression, fixed-effects, and random-effects models was estimated. Also, the generalised method of moment estimator was employed to address the problem of endogeneity, usually associated with panel data analysis and as a robustness check for the model. The logit regression model was used to examine the determinant factors of IFRS adoption.Various statistical tests were estimated, such as the diagnostic test, using the histogram and Jarque-Bera statistics, difference-in-difference (DID) test, the unit root test, and the cross-sectional dependence test. The Hausman's chi-square was estimated to determine the best alternative technique between the fixed-effects and random-effects models. Also the Arellano-Bond estimator autocorrelation 〈1〉 and 〈2〉 was used to evaluate the validity of the variable instruments in the model. Besides, the average marginal effect (AME) was estimated for the effect of each covariate on the result. Certain covariates were estimated as control variables in the model.The statistical results show a significant and positive effect of the adoption of IFRS on FPI inflows after the adoption and implementation of IFRS in adopting countries. Equally, the finding further indicates a significant difference in the volume of FPI inflows after the adoption of IFRS than before the adoption, in adopting countries. The statistical estimates also reveal a positive and significant effect of IFRS adoption on FPI in adopting countries, compare with non-adopting IFRS countries where it shows a negative and non-significant relationship. It shows that countries that adopted IFRS experience more inflows in FPI compare with the non-adopting countries in Africa.Furthermore, the logit regression results show that culture, the legal system, political system, investor protection, market capitalisation, and tax were found to be positively significant with the probability of adopting IFRS in the logistic model. This thesis, therefore, suggests that the adoption of IFRS is justified in the selected countries in Africa since the results indicated a positive and significant effect of IFRS adoption on FPI in these countries. Hence, substantiated the assumption of IFRS proponents that adoption will enhance the flow of FPI in adopting countries for economic development. Policies measure to monitor the activities of listed firms and to enforce compliance with IFRS rules and regulations are warranted.These policies would further enable IFRS adopting countries to enhance more flow of FPI.