CHAPTER ONE

INTRODUCTION

1.1 Background to the study

Fraud as defined by W. Steve Albrecht (2003) in his book Fraud Examination and Prevention is a representation about a material fact which is false and intentionally or recklessly so, which is believed and acted upon by the victim, to the victim’s damage.

The term “fraud” in the broadest sense has come to mean an intentional deception made for personal gain or to damage another individual, while the term “corporate fraud” is described as a fraud occurring within an organization and involving deliberate dishonesty to deceive the public, investors or lending companies, usually resulting in financial gain to the criminals or organization. Fraud differs from unintentional errors because fraud has elements of intent and purpose of gaining an advantage over another through false pretense. Fraud is considered as a pervasive business risk and in fact an inherent risk of engaging in business. Many organizations have responded by developing fraud detection strategies and today there is a deluge in corporate fraud. Often corporate fraud is difficult to detect due to several reasons:

• Perpetrators may be familiar with accounting procedures and hence they have the ability to cover up the fraud.
• Auditors may lack adequate training in the nature of fraud and investigative methodologies. The association of certified fraud examiners (ACFE) the world’s largest anti-fraud literature and providing training and education, but it has still a long way to go in practice.
• The time and budgetary constraints associated with external audit results in external auditors increasing their reliance on management’s representations of financial statements.
• External auditors can experience an agency problem of an inherent conflict of interest because they are investigating the party that paid for their services, thus creating built in conflict for auditors.

The primary emphasis of this study is on major fraud perpetrated to the detriment of the organization for personal gain by individuals occupying positions of trust and influence in management positions. The secondary emphasis is on management fraud for the benefit of the organization with a focus on the interrelationship between fraud for and against the organization. It goes without saying that fraud for the organization invariably involves some personal benefits for the perpetrator.

On hearing the phrase, “major management fraud,” an internal auditor’s first thought is usually about fraudulent financial reporting. However, there are other kinds of management fraud:

• Fraudulent financial reporting (fraud for the organization).
• Internal misappropriation or corruption (fraud against the organization).
• Some other fraud for the organization include (various forms of bribery and corruption, and money laundry.

Fraud, auditing, forensic accounting and/or fraud investigation (i.e forensic accounting) put things together rather than taking them apart, as in the case in classic financial auditing or the modern method of systems analysis. The process of forensic accounting is also sometimes more intuitive and deductive although both intuition and deduction play important parts. Financial auditing is more procedural in many regards and is not intended to work as effectively in detecting frauds as the tenets of fraud auditing and forensic accounting.

In the book fraud Auditing and Forensic Accounting (3^rd Edition) by Tomme and Aaron SINGLETON, Jack Bologna and Robert Lindquist, the term forensic accounting refers to the comprehensive view of fraud investigation. It includes the audit of accounting records to prove or disprove fraud. If includes the interview process of all related parties to a fraud, when applicable. And it includes the act of serving as an expert witness, when applicable. webster’s Dictionary defines the word forensic as “belonging to, used in, or suitable to court of judicature or to public discussions and debate”.

Accordingly, the term forensic in the accounting profession deals with the relation and application of financial facts to legal problems. Forensic accounting evidence is oriented to a court of law.

The involvement of the forensic accountant is almost always reactive, this distinguishes forensic accountants from fraud auditors, who tend to be actively involved in fraud prevention and detection.

Fraud cases have significantly increased and continued to gain prominence. Following the well- renown fraud cases such as Enron and WorldCom that had their earnings decreased by billions (Graham et al., 2008), recent cases such as Tesco, JP Morgan and Green Mountain.

Coffee have caused severe erosion of shareholder confidence in capital markets and drawn public attention to the criticality of fraud (Peterson and Buckhoff, 2004; Rezaee and al., 2004).

Financial statement fraud is one of the main classes of fraud and is defined as “the material omissions or misrepresentation resulting from an intentional failure to report financial information in accordance with generally accepted accounting principles” (Nguyen, 1995). It includes malpractices such as fabricating or altering records, documenting bogus transactions, omission of transactions or events from records, and masquerading substantial information (Stolowy and Breton, 2004). Financial statement fraud or financial misstatements which are the focus of this study are distinguished from unintentional financial misrepresentations such as accounting errors.

The global fraud survey by The Association of Certified Fraud Examiners (ACFE, 2020) documented that fraudulent financial reporting is the least common (10% of schemes) but the costliest form of fraud. It is reported that each occupational fraud case would incur a median cost of $125,000 over a median period of 14 months. Whilst asset misappropriation and corruption happen more frequently than financial statement fraud, the impact of the latter crime is considerably greater in magnitude. Financial statement fraud cases alone reported a median loss of $954,000 with a median period of 24 months.

Generally, financial statement fraud results in the impairment of a firm’s productivity, operational efficiency, and innovation. It shifts resources to unproductive business projects, restricts a firm’s prospect to grow, reduces a firm’s equity value and places a company in a risky position of being delisted from the stock exchange (Rezaee, 2005). Over the last two decades, a projected amount of $5.127 trillion has been incurred being the financial repercussions from fraud activities that have occurred worldwide. This phenomenon is associated with the rise in related losses by 56% in the last ten years (Gee and Button, 2019). The true underlying costs of fraud might be greater when considering the indirect costs suffered, such as the credibility damage faced by creditors, employees and investors, including the destruction of business reputation caused by the accounting scandals. The eventual bankruptcy and delisting of companies exacerbated the situation (Craja and al., 2020).

The deployment of an effective fraud detection strategy is crucial due to the costly and catastrophic nature of fraud. Fraud detection further facilitates fraud prevention. As firms continually improve fraud detection methods, employees become more certain that fraud will be detected, thus discouraging them from committing fraud in the future. (Ngai and al., 2011) highlight that the detection of financial statement fraud allows decision makers to design suitable measures to minimize the effect of fraud and generate an average yearly gain in profit ranging from 10 to 40 percent. It is also contended that the long-term benefits of implementing fraud prevention and detection control measures outweigh the associated costs (Hopwood and al.,2012).

The statement of Auditing Standards (SAS) No. 82 issued by the American Institute of Certified Public Accountants (AICPA) highlights the responsibility for detecting fraudulent activities lies heavily with the auditors. Nonetheless, no specific guidelines on detecting fraud                 were provided, regardless of the task being complicated for the auditors. Based on the ACFE 2020 report, external and internal auditors detected only a limited number of fraud incidences, at rates of 4% and 15% and 4% respectively (ACFE, 2020). Superseding SAS No. 82, SAS No. 99 established a framework for addressing weaknesses in  fraud detection processes, with the aim of boosting auditor quality and effectiveness in detecting fraud via assessment of fraud risk factors in companies. Nevertheless, despite reforms of accounting and auditing standards, a new anti-fraud laws being enacted to combat the prevalent cases of fraudulent financial reporting, numerous firms’ anti-fraud measures are rather superficial and outdated (Anderson, 2004). The commonly applied red flag approach, which entails a checklist of fraud warning signals, is deemed ineffective.  Krambia-Kardis (2002) argued that red flags do not indicate the occurrence of fraud incidences. It is further contended that red flags approach suffers from two main drawbacks, i.e.

• There is an association between red flags and fraud, however, the association is imperfect, and
• Red flags put emphasis on specific cues which prevent auditors from discovering other causes of fraud.

The detection of fraudulent financial reporting cases is very challenging in view of the contemporary business environment, which is very much information-oriented, with complex and dynamic business operations and systems (Chen and al., 2019). The use of automated systems for detecting fraudulent financial reporting has gained increasing attention as a result of the application of computer-assisted mechanisms to commit fraud and the evolution of technologies used to evade fraud detection (SEC,2019). These automated systems for fraud detection are critical, especially for auditors, since they enhance the pace and accuracy of auditing (Abbasi and al., 2012; Albrecht et al. 2008). A faster and efficient fraud detection strategy can substantially reduce the magnitude and loss of fraud (ACFE, 2020). In addressing this issue, significant attempts have been undertaken to develop intelligent systems capable of detecting financial statement fraud.

Forecasting business and economic activity, and particularly fraud event prediction, is almost always difficult owing to the degree of uncertainty surrounding the activities. It is asserted that the possibility of prediction inaccuracy creates a massive problem for decision-and policy-makers alike (Makridakis and al.,2009). On the one hand, acknowledging the limitations of prediction accuracy may indicate an inability to gauge associated uncertainty and decision accuracy. Accepting the possibility of accurate prediction, on the other hand, would mean surrendering to shocks and illusions of control, both of which may have catastrophic consequences.

Goodwin and Wright (2010) discuss factors that contribute to the difficulty of predicting uncommon occurrences such as fraud. Firstly, when the data contains a huge number of comparable occurrences (large reference class), prediction improves due to the ability to relative frequency information. Whilst a large reference class is related to large sample sizes, it is feasible to obtain a highly precise assessment of the underlying probability distribution. It is also possible to avoid biases in judgment since a large reference class can be assessed using statistical analysis throughout the estimation process. In contrast, constructing a relative frequency-based probability for a rare event, for instance, financial crisis or fraud, is hence more challenging due to its small reference class is related to large sample sizes, it is feasible to obtain a highly precise assessment of the underlying probability distribution. It is also possible to avoid biases in judgment since a large reference class can be assessed using statistical analysis throughout the estimation process. In contrast, constructing a relative frequency-based probability for a rare event, for instance, financial crisis or fraud, is hence more challenging due to its small reference class.

Secondly, a prediction model may simplify the actual system and may fail to embed the complex interactions between the system’s various distinct components. This is mostly relevant in models of the economy, the human body and weather systems (Orrell and McSharry,2009). Small modifications in any of the system’s components may cause an amplified impact due to the intricate interplay of the system’s components. This may lead to underestimation by the prediction model of the actual arrays of uncertainty, resulting in probabilities that are inaccurately estimated.

Thirdly, the fundamental assumption of most prediction models is causal relationship between variables. Nonetheless, despite general acceptance among experts in the field, the coherent theory of causality does not prove the reality of causation. Correlations may be illusory or the result of unknown spurious factors. (Hamilton and Rose, 1980) particularly when involving human judgement, or they may be applicable only under specific circumstances pertinent to the specific reference data. Nonetheless, the misconception that strong correlation implies causality may significantly influence one’s reasoning.

Finally, human judgment is often used to estimate the probability of a rare event happening, particularly when the reference class has insufficient event cases for statistical analysis.

Tversky and Kahneman (1974) assert that individuals employ basic mental strategies or heuristics in dealing with the complexities of probability estimation. While heuristics may result in good estimates at times, they can also result in systematic bias in judgments.

Based on the above factors, it can be concluded that catastrophic rare fraud events can be hardly predictable. However, efforts to develop a detection tool capable of alerting interested parties to fraud perpetrators or financial fraud cases remain crucial in order to bring red flags of fraudulent activities to the attention of interested parties at an early stage. The continual attempts to develop a fraud detection model may allow for incremental improvement of previous detection models’ shortcomings. This may improve the accuracy of future fraud predictions.

Traditional methods of fraud detection depend heavily on conventional approaches such as auditing, which are less efficient due to the complexity of the fraud case. Data mining-based techniques have been found to be more effective in detecting fraud due to their capacity of identifying small anomalies in big data sets (Ngai and al., 2011). The two main types of data mining are statistical and computational. Statistical methods are those traditional mathematical techniques, such as Bayesian theory and regression, whereas computational techniques refer to modern intelligence technique, such as support vector machines and neutral networks. The way the statistical method operates is relatively inflexible compared to the computational methods that can learn from and adapt to the problem domain (West and Bhattacharya, 2016). There is a challenge in that the more executives who engage in financial fraud are aware of the software and techniques available for fraud detection, the more likely they are to adapt their fraud tactics and evade detection, particularly by currently available techniques (Zhou and Kapoor, 2011). New innovative techniques are urgently required that are both efficient and effective in keeping up with these adaptive and potentially newly emerging financial scams. Future studies may explore detection techniques that could orient the program in response to a firm’s specific conditions. A model for detecting fraud may not provide the best prediction when using merely historical financial statement data to identify fraud (Sharma and Panigrahi, 2012). Hence, studies may consider including the analysis of governance factors since it has been argued that the deficiencies in corporate governance mechanisms have led to the wave of corporate financial scandals (Fich and Shivdasani, 2007). Moreover, exogenous parameters inclusive of internal firm-specific factors and external factors related to the economy, industry and institutional environment would provide more accurate financial fraud predictions and detection.

How pervasive is business fraud? How likely is it to be discovered either by audit design or by accident? Research in the last ten years has been able to reveal both the scope of fraud and the most effective means of detecting frauds. The various ACFE RTTNs have also measured the common methods of detecting fraud. According to the reports, tips and complaints have consistently been the most effective means of detecting frauds, and are a much higher percentage than the method ranked second. Tips and complaints accounted for 46.2 percent of the initial detection of occupational fraud in the 2008 report. Internal Controls has second (23.3 percent), Internal audit was third (20 percent), accident was fourth (19.4 percent) and external audit was fifth (7.1 percent). Interestingly, while generally the percentages have not changed much over time, internal control has gained potentially suggesting the emphasis placed on controls (particularly including Sarbanes-Oxley) may be improving fraud detection. Thus, the best detection methods are; tips, internal controls, and internal audit. All of these are integral tenets of the Sarbanes-Oxley Act of 2002 and associated auditing standards.

A key aspect of preventing and detecting fraud is to understand the profile of typical fraudsters, by type. Regarding asset misappropriation, the person is usually someone who was not suspected, oftentimes least suspected. The profile of white-collar criminals is very different from blue collar criminals, or street criminals. This fact makes fraud even more difficult to prevent or detect.

1.2 Statement of the Problem

Statutory Audit is an audit required by law as to lay credence to financial statement and ensure that adequate and proper financial records have been maintained as required by statutes are GAAP and regulation (Eyisi & Ezuwore, 2014).

External auditing by law is required to be appointed by sharedholders most times the management on behalf of the shareholders appointment the external auditor whose book of account is being examined (audited). In view of the above it can be said that the mode of appointment of the external auditor has negatively affected governance function effectively thereby making investors to lose confidence in annual corporate reports of companies (Lee and Walker, 2001). An instance of this could be drawn from Arthur Anderson of Enron and Worldcom Auditors who were indicted for obvious fraudulent financial statement which affected investors and economy of US (Zimbleman and al., 2012). The issue of fraud in corporate governance can be reduced by use of forensic auditors. The forensic auditor with his special skills (that is Analytical, Communication and Technological skills) can reduce fraud and improve corporate governance by instilling fear both to the management and their employees when carrying out his audit function (Eyisi & Ezuqore, 2014)

According to SAS 99, external audits are provided guidance that has the potential to improve audit quality in detecting material financial misstatements whether caused by fraud or error. SAS No 99 includes the suggestion that an “auditor may respond to an identified risk of material misstatement due to fraud by assigning forensic specialist (AICPA 2002). The Enron saga recorded that its officers had used creative accounting practices to conceal about $600 million in financial losses over a period of three years 1997 – 2000 which led to a crisis of confidence in the stock market. Worldcom, another American giant used creative accounting to reclassify and amortize revenue expenses amounting to $3.85 billion over a long period of the time consequently the company went for chapter ii bankruptcy protections. There are many corporate entities misadventures typified by such practices of using doubtful and questionable accounting practices  to conceal huge losses, concealing extensive borrowing by keeping them off the balance sheet and consequently overall fraudulent reporting.

The anti-corruption group, Transparency international has consistently ranked Cameroon among countries most riddled with corruption. It described Cameroon as a Gangster’s paradise where you pay a bribe to see key official in many establishments. You pay a bribe to get a job. You pay a bribe to get the passport that is yours by birthright. If you do not give or collect bribes, you remain poor or an object of scorn despite your several degrees and cognate experience until providence intervenes for you “(TI, 2000).

Other HDI for Cameroon include life expectancy 61-62. 7 years (who Data); Education index 0.410; Multir-Dimensional Poverty index 0.302; and Gross National Income Per Capita 2.132. current statistics reveal that less than 10% of Cameroon’s population, enjoy the privileges of its numerous natural resources (minerals, forest reserves and agricultural producers etc). Thus 80% and above of Cameroonians are languishing in poverty. Cameroon is the 37^th poorest country in the world out of 189 countries according to the Human development Index. Therefore, fraud is systemic in Cameroon with the ordinary citizen being compelled to be a liar, cheat or an outright thief. Cameroon is the 37^th poorest country in the world out of the 189 countries fraud has growth and national development, subverted the nation’s values and norms future the cradle of our father. Today, the nation faces the trauma of a state whose date with destiny has been put on hold, for reasons that are completely self-made and completely avoidable.

According to Osisioma (2012) the global financial meltdown was made possible because there was a failure on the part of gate keepers including the auditors. This has brought the indispensable corporate accountant into disrepute and ridicule and a crisis hour for the accountancy profession. New face of crime is mitigated by well-articulated and professionally executed central schemes of an investigative, auditing and accounting nature? Of course, this led to a development of regulatory landscape for accountancy profession with new emphasis on forensic accounting. Accounting procedure simply makes historic reporting or recording while auditing verifies and validates the accuracy of such recording. The auditor by the scope of his work cannot pontificate with any level of finality that fraud has occurred or not.

A series of studies have been carried out to provide an understanding of the reasons of the rising spate of fraud and fraudulent activities and their incidences (Okaye & Akamobi 200, Owojori & Asaolu, 2009, Izedomin & Mgbane, 2011, Kasum 2009). Indeed, modugu and Anyaduba (2013) submitted that financial irregularities have become the specialty of both private and public sectors as individuals perpetrated fraud and corrupt practices according to the capacity of their office. Consequently, there is great expectation that forensic accounting may be able to stem the tide of financial malfeasance witnessed in most sectors of the economy.

However, there has not been adequate emphasis, especially survey evidence on how forensic accounting can help curtail creative accounting beyond the several general views that abound. Consequently, this present study fills this gap that exist in empirical investigation to the extent to which forensic accounting can help curb creative accounting, with specific focus on ENEO in Mezam division. Mezam division is used as the focus of study for this research work to highlight the impact of the prevailing socio-economic disruptions in irregular financial practices.

In the face of bourgeoning cases of fraud and malfeasance in business entities such as ENEO, it becomes important to empirically examine the techniques of these “fraudulent reporting messiahs” so as to determine the efficacy of such techniques and skills on their mission of providing financial reporting and wiping the stigma on the accounting profession.

Management is accountable to shareholders, and other stakeholders. Management of companies are said to be solely responsible for preparing accounts and maintaining adequate financial records (Millchamp, 2002). More so, they are responsible for detecting and preventing fraud in their organizations, while the external auditor’s responsibility is to ensure that accounts prepared by company’s management are in line with general accepted accounting principles (GAAP) and statute. The external auditor has failed to accept responsibility to detect fraud, although SAS SS requires the external auditor to report material misstatement and errors due to fraudulent activities. Ramaswamy, (2009) states that there is a great need for skilled professionals that can identify, expose and prevent weaknesses in three key areas. Poor corporate governance, feared internal controls and fraudulent financial statement.

Nevertheless, the above responsibility has not been accepted by auditors, thus resulting to corporate fraud and most often corporate failure and poor corporate governance. In order to ensure proper accountability and prevent fraud by the management, the forensic auditor being an expert in financial fraud matters with special skills in scientific knowledge and legal matters have helped management to improve their role by providing software packages which enable management to easily detect and prevent fraudulent activities. The directors being aware that the forensic auditors maybe invited to detect and prevent fraudulent activities,  will ensure that their organization has a good internal control system, checks and balances which are transparent, thereby positively influencing corporate governance (Eyisi & Ezuwore, 2014).

1.3 Research Questions

The following research questions were formulated to guide the study;

1.3.1 Main Research Question.

What is the relationship between engaging forensic accountants and fraud auditors in curbing fraud and corruption at ENEO.

1.3.2 Specific Research Questions.

1) What extent is conducting forensic investigation effective in financial fraud detection at ENEO.

2) What extent is analyzing financial transactions effective in financial fraud detection at ENEO.

3) What extent is forensic examination of incomplete or creative accounting recoeds effective in detecting financial fraud at ENEO.

1.4 Research Objectives

The research objectives are subdivided into main and specific objectives;

1.4.1 Main Research Objectives

The main objective of this study is to analyze and evaluate the work of a forensic accountant at ENEO.

1.4.2 Specific Objectives

1) To identify the various corporate frauds and the means of their occurrence.

2) To know the various forensic accounting techniques to detect fraud.

3) To understand the role of forensic accounting in providing a solution to such frauds.