Corporate failure and ethical resources: a case study of Steinhoff and Carillion
- Authors: Mthombeni, Seyijeni Koos
- Date: 2023-10-13
- Subjects: Corporate governance , Business ethics , Steinhoff International (Firm) Corrupt practices , Carillion (Firm) Corrupt practices , Business failures , Accounting fraud
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/419165 , vital:71621
- Description: This study aimed to investigate the impact of disregarding ethical resources on company performance, with a particular focus on Carillion and Steinhoff as case studies. A pragmatist research philosophy was employed using a mixed methods approach, utilizing deductive inferencing to produce archival research. Data was collected from annual financial statements and existing literature on Steinhoff and Carillion's corporate failures. Both content analysis and statistical analysis were employed to analyse the data. The study found that both Carillion and Steinhoff were at the top of their respective industries when they began to underperform due to poor governance. On the part of Carillion, much of its failure can be attributed to aggressive bidding, while for Steinhoff, its failure was due to unscrupulous accounting practices. Corruption and fraud at the top echelon of each of these respective companies began to trickle down to the bottom of the hierarchy. Additionally, Steinhoff used a two-tier board system that promotes information asymmetry between a management board and a supervisory board. This gave Steinhoff’s management board leverage to manipulate company reports and hide information from the supervisory board. Steinhoff equally violated the board’s independence by making former management executives part of the supervisory board, who could potentially be lenient to the management board due to past relationships. This was further exacerbated by the CEO duality, which contributed to Steinhoff’s lack of board independence. Furthermore, Steinhoff’s board was reported to have served as board members for a long time, eventually leading them to create a group culture that negatively affected its board’s independence. Different from Steinhoff, which lacked board independence and board diversity, at face value, Carillion appeared to have a predominantly independent board with diverse experience and external commitments. However, Carillion also lacked board independence in a different way, as some of its board members were previously employed by KPMG. KPMG was also the external auditor of Carillion. This created a scenario where Carillion and KPMG were conniving, which may have affected the objectivity of the external audits on financial performance. Further to this, the CEO held outsized power over the board, which could have also resulted in a lack of independence. This, in turn, facilitated corrupt behaviour within the organisation, which may have contributed to its corporate failure. iv The findings of the study highlight the following three conclusions: i) profits that are premised on reckless, irregular, and fraudulent business and accounting practices are not sustainable; ii) governance structures that do not adhere to sound corporate governance principles result in impaired board independence and negatively affect firm performance; and iii) companies that reach the pinnacle of their success through unethical conduct are ultimately short-lived. , Thesis (MBA) -- Faculty of Commerce, Rhodes Business School, 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Mthombeni, Seyijeni Koos
- Date: 2023-10-13
- Subjects: Corporate governance , Business ethics , Steinhoff International (Firm) Corrupt practices , Carillion (Firm) Corrupt practices , Business failures , Accounting fraud
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/419165 , vital:71621
- Description: This study aimed to investigate the impact of disregarding ethical resources on company performance, with a particular focus on Carillion and Steinhoff as case studies. A pragmatist research philosophy was employed using a mixed methods approach, utilizing deductive inferencing to produce archival research. Data was collected from annual financial statements and existing literature on Steinhoff and Carillion's corporate failures. Both content analysis and statistical analysis were employed to analyse the data. The study found that both Carillion and Steinhoff were at the top of their respective industries when they began to underperform due to poor governance. On the part of Carillion, much of its failure can be attributed to aggressive bidding, while for Steinhoff, its failure was due to unscrupulous accounting practices. Corruption and fraud at the top echelon of each of these respective companies began to trickle down to the bottom of the hierarchy. Additionally, Steinhoff used a two-tier board system that promotes information asymmetry between a management board and a supervisory board. This gave Steinhoff’s management board leverage to manipulate company reports and hide information from the supervisory board. Steinhoff equally violated the board’s independence by making former management executives part of the supervisory board, who could potentially be lenient to the management board due to past relationships. This was further exacerbated by the CEO duality, which contributed to Steinhoff’s lack of board independence. Furthermore, Steinhoff’s board was reported to have served as board members for a long time, eventually leading them to create a group culture that negatively affected its board’s independence. Different from Steinhoff, which lacked board independence and board diversity, at face value, Carillion appeared to have a predominantly independent board with diverse experience and external commitments. However, Carillion also lacked board independence in a different way, as some of its board members were previously employed by KPMG. KPMG was also the external auditor of Carillion. This created a scenario where Carillion and KPMG were conniving, which may have affected the objectivity of the external audits on financial performance. Further to this, the CEO held outsized power over the board, which could have also resulted in a lack of independence. This, in turn, facilitated corrupt behaviour within the organisation, which may have contributed to its corporate failure. iv The findings of the study highlight the following three conclusions: i) profits that are premised on reckless, irregular, and fraudulent business and accounting practices are not sustainable; ii) governance structures that do not adhere to sound corporate governance principles result in impaired board independence and negatively affect firm performance; and iii) companies that reach the pinnacle of their success through unethical conduct are ultimately short-lived. , Thesis (MBA) -- Faculty of Commerce, Rhodes Business School, 2023
- Full Text:
- Date Issued: 2023-10-13
The classification performance of ensemble decision tree classifiers: a case study of detecting fraud in credit card transactions
- Authors: Chogugudza, Mcdonald
- Date: 2022-11
- Subjects: fraud , Commercial fraud , Accounting fraud
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/27590 , vital:69317
- Description: In this dissertation, we propose ensemble decision tree classifiers as an ideal classification technique for solving the problem of fraud in the domain of credit card transactions. Ensemble tree classifiers have been applied in many areas like speech recognition, image recognition and medical diagnostics and have shown excellent results. At the centre of fraud, credit card fraud has been a major concern. The rise in credit card fraud is largely attributed to the nature in which it can be done. A fraudster does not need to always be physically present to commit fraud making it the number one target for criminals. Card-Not-Present refers to this type of fraud where an electronic transaction can be conducted without the need for a client to be present. This can be done via telephonic calls or the web. To be able to come up with better classifiers it was important for the researcher to first investigate what causes misclassifications in fraud detection systems. A systematic literature review was done to uncover the factors that have been identified as causes of misclassifications. It was discovered that many factors lead to misclassifications and several authors have proposed techniques to handle these factors. However, there is no universal techniques for addressing factors that lead to misclassifications as different domains have different datasets which require different techniques. This study investigates how parameters involved in modelling fraud detection systems impact the classification performance of ensemble decision tree classifiers. The factors that were investigated include sample size, sampling technique, learning method and choice of split criterion and how they affect classification performance. A series of experiments were conducted to investigate how the aforementioned factors contributed to better classifiers. Ecommerce data from Vesta corporation made available on Kaggle was used in the experiments. The data was split into two sets, one for training the models and the other for testing the performance of the models. Accuracy, confusion matrix, precision and recall were used as performance measures. Our results showed that a larger sample size resulted in better classifiers. This is attributed to models having more instances to learn from which covers most patterns of fraudulent transactions. The sampling technique was shown to be pivotal in classification performance as under sampling showed a great reduction in performance as it achieved a maximum accuracy of 89.6223 while oversampling produced increased performance with maximum accuracy of 99.9531. Furthermore, our results showed that the choice of split criterion impacts the performance of ensemble tree classifiers. The use of entropy as the choice of split criterion resulted in better classifiers compared to the use of the Gini index. However, the downside is that entropy requires more time to execute compared to the Gini index. Lastly, the learning method proved to impact the performance of ensemble classifiers. Models that used supervised learning had better performance compared to those that use unsupervised learning in detecting credit card fraud. The conclusions from this research are insightful when designing fraud detection systems that use ensemble decision tree classifiers as base learners. , Thesis (Msci) -- Faculty of Science and Agriculture, 2022
- Full Text:
- Date Issued: 2022-11
- Authors: Chogugudza, Mcdonald
- Date: 2022-11
- Subjects: fraud , Commercial fraud , Accounting fraud
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/27590 , vital:69317
- Description: In this dissertation, we propose ensemble decision tree classifiers as an ideal classification technique for solving the problem of fraud in the domain of credit card transactions. Ensemble tree classifiers have been applied in many areas like speech recognition, image recognition and medical diagnostics and have shown excellent results. At the centre of fraud, credit card fraud has been a major concern. The rise in credit card fraud is largely attributed to the nature in which it can be done. A fraudster does not need to always be physically present to commit fraud making it the number one target for criminals. Card-Not-Present refers to this type of fraud where an electronic transaction can be conducted without the need for a client to be present. This can be done via telephonic calls or the web. To be able to come up with better classifiers it was important for the researcher to first investigate what causes misclassifications in fraud detection systems. A systematic literature review was done to uncover the factors that have been identified as causes of misclassifications. It was discovered that many factors lead to misclassifications and several authors have proposed techniques to handle these factors. However, there is no universal techniques for addressing factors that lead to misclassifications as different domains have different datasets which require different techniques. This study investigates how parameters involved in modelling fraud detection systems impact the classification performance of ensemble decision tree classifiers. The factors that were investigated include sample size, sampling technique, learning method and choice of split criterion and how they affect classification performance. A series of experiments were conducted to investigate how the aforementioned factors contributed to better classifiers. Ecommerce data from Vesta corporation made available on Kaggle was used in the experiments. The data was split into two sets, one for training the models and the other for testing the performance of the models. Accuracy, confusion matrix, precision and recall were used as performance measures. Our results showed that a larger sample size resulted in better classifiers. This is attributed to models having more instances to learn from which covers most patterns of fraudulent transactions. The sampling technique was shown to be pivotal in classification performance as under sampling showed a great reduction in performance as it achieved a maximum accuracy of 89.6223 while oversampling produced increased performance with maximum accuracy of 99.9531. Furthermore, our results showed that the choice of split criterion impacts the performance of ensemble tree classifiers. The use of entropy as the choice of split criterion resulted in better classifiers compared to the use of the Gini index. However, the downside is that entropy requires more time to execute compared to the Gini index. Lastly, the learning method proved to impact the performance of ensemble classifiers. Models that used supervised learning had better performance compared to those that use unsupervised learning in detecting credit card fraud. The conclusions from this research are insightful when designing fraud detection systems that use ensemble decision tree classifiers as base learners. , Thesis (Msci) -- Faculty of Science and Agriculture, 2022
- Full Text:
- Date Issued: 2022-11
The auditor's duty of reasonable care and skill and the expectation to detect fraud
- Kujinga, Benjamin Tanyaradzwa
- Authors: Kujinga, Benjamin Tanyaradzwa
- Date: 2008
- Subjects: Auditing Standards , Accounting fraud , Financial statements -- Law and legislation
- Language: English
- Type: Thesis , Masters , LLM
- Identifier: vital:11115 , http://hdl.handle.net/10353/104 , Auditing Standards , Accounting fraud , Financial statements -- Law and legislation
- Description: Auditors perform a very important task within the context of the affairs of a company because financial reporting can only serve its purpose if stakeholders can rely on its accuracy and reliability. An auditor’s duty is to opine whether an entity’s financial reporting has been done according to the requirements of the law. The responsibility of reporting according to the law lies with an entity’s directors. Auditors cannot issue an absolute assurance as to the lawfulness and reliability of an entity’s financial reporting. However when it is subsequently discovered that the financial reporting was incorrect and that fraud has occurred auditors are often blamed and sued for enormous amounts of money for failing to detect material anomalies in the financial reports. These actions are based on the fact that auditors have a duty to exercise reasonable care and skill in the performance of their duties and through their failure to act as such, have caused financial harm to the clients or third parties. The fact that auditors are only required by law to exercise reasonable care and skill and perform an audit according to the standards of the reasonable auditor and not the most meticulous one, is often not regarded or is sometimes deliberately ignored. This clearly represents a problem in our law, namely that the presence of fraud in financial reports does not in itself suggest negligence on the part of the auditor but is apparently often perceived to do so. This research shows that the auditor’s duty of reasonable care and skill does not necessarily entail the duty to detect fraud. The elements of the duty of reasonable care and skill are identified from case law, legislation and international auditing standards. In order to limit the liability of auditors in general it is important to focus also on the elements of fault (negligence), wrongfulness and causation. This research shows that negligence cannot be established merely by the presence of fraud or material misstatements in financial statements. The responsibility for fair financial reporting lies with the directors. This research gives prominence to this fact which often seems to be ignored for convenience and in order to place the blame on the auditors. This research implicitly asks the question, why are auditors being held responsible for material misstatements in a company’s financial statements and not the directors? Guidelines for determining the extent of an auditor’s liability in this regard are formulated in this research.
- Full Text:
- Date Issued: 2008
- Authors: Kujinga, Benjamin Tanyaradzwa
- Date: 2008
- Subjects: Auditing Standards , Accounting fraud , Financial statements -- Law and legislation
- Language: English
- Type: Thesis , Masters , LLM
- Identifier: vital:11115 , http://hdl.handle.net/10353/104 , Auditing Standards , Accounting fraud , Financial statements -- Law and legislation
- Description: Auditors perform a very important task within the context of the affairs of a company because financial reporting can only serve its purpose if stakeholders can rely on its accuracy and reliability. An auditor’s duty is to opine whether an entity’s financial reporting has been done according to the requirements of the law. The responsibility of reporting according to the law lies with an entity’s directors. Auditors cannot issue an absolute assurance as to the lawfulness and reliability of an entity’s financial reporting. However when it is subsequently discovered that the financial reporting was incorrect and that fraud has occurred auditors are often blamed and sued for enormous amounts of money for failing to detect material anomalies in the financial reports. These actions are based on the fact that auditors have a duty to exercise reasonable care and skill in the performance of their duties and through their failure to act as such, have caused financial harm to the clients or third parties. The fact that auditors are only required by law to exercise reasonable care and skill and perform an audit according to the standards of the reasonable auditor and not the most meticulous one, is often not regarded or is sometimes deliberately ignored. This clearly represents a problem in our law, namely that the presence of fraud in financial reports does not in itself suggest negligence on the part of the auditor but is apparently often perceived to do so. This research shows that the auditor’s duty of reasonable care and skill does not necessarily entail the duty to detect fraud. The elements of the duty of reasonable care and skill are identified from case law, legislation and international auditing standards. In order to limit the liability of auditors in general it is important to focus also on the elements of fault (negligence), wrongfulness and causation. This research shows that negligence cannot be established merely by the presence of fraud or material misstatements in financial statements. The responsibility for fair financial reporting lies with the directors. This research gives prominence to this fact which often seems to be ignored for convenience and in order to place the blame on the auditors. This research implicitly asks the question, why are auditors being held responsible for material misstatements in a company’s financial statements and not the directors? Guidelines for determining the extent of an auditor’s liability in this regard are formulated in this research.
- Full Text:
- Date Issued: 2008
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