CHAPTER 1: INTRODUCTION

1.1 INTRODUCTION

An external audit of financial statements (hereafter “an audit” for this research study) is a significant contributor to the overall economy (Osim, Goddymkpa & Nsima, 2020). It is performed with the sole purpose of reporting if financial statements were prepared in accordance with the financial reporting framework (The International Auditing and Assurance Standards Board [IAASB], 2014). When these financial statements lack accuracy, contain errors or omissions, or are even misleading, the public that relies on these financial statements may make misinformed and/or incorrect economic decisions (Salih & Flayyih, 2020).

Over the years, the world has witnessed instances where external auditors have issued unqualified or “clean” audit opinions for entities which collapse afterwards due to irregularities and/or fraud which is subsequently revealed in these entities, a term Osim et al. (2020) defines as “audit failure”. This definition of the term is elaborated on by Smith and Marx (2021), who state that audit failure are frequently linked to company failures and dishonest financial reporting. In many cases, it is thought that the auditors violated their obligation to serve as the “watchdog” for those who utilise financial statements by allowing fraudulent acts to go unnoticed (Smith & Marx, 2021). A

Osim et al. (2020) describe how the effects of corporate failures are often felt by stakeholders, investors or shareholders, as billions are lost in the financial value chain when these companies collapse. This statement is echoed by Cole, Johan and Schweizer (2021), when they state that financial instability or scandals cause company failures, which have severe negative effects on all parties involved, including the general public, workers, auditors, creditors, business partners, capital markets, investors, and regulators.

1.2   BACKGROUND TO THE RESEARCH PROBLEM

To respond to corporate failures, audit quality concerns and the rapidly changing IT environment in the financial reporting value chain and to improve audit quality, more auditors are utilising data analytics techniques (Earley, 2015). This is because using data analytics for audits raises the quality of such audits (Kandeh & Alsahli, 2020; Gao, Huang & Wang, 2021).

Over the past ten years, auditors have increasingly used data analytics tools in audits (Maniar, n.d.; Ramlukan, 2015). Murphy (2015) echoes this when highlighting that over the past 20-30 years, auditors have been using more technology in an audit. Earley (2015) stated that this debunks the myth that audit and accounting firms do not employ data analytics throughout the external auditing process. However, it is also argued that more internal auditors, as opposed to external auditors, have been utilising data analytics in performing their internal audits. On the other hand, Maniar (n.d.) and the FRC (2017) argue that auditors are still not fully utilising data analytics tools in an audit.

Auditors are using data analytics tools to, among other things, obtain an extensive understanding of their clients’ businesses (Earley, 2015). Similarly, Mazzei, Ramlukan and Sharma (2015) state that understanding the business, including the assessment of risk performed in an audit, has been made simpler by utilising data analytics, which provides auditors with a thorough understanding of the entity. Additionally, as a result, auditors broaden the scope of the items they audit. Botez (2018) supports this by stating that using traditional sampling methods to obtain audit evidence as required by auditing standards changes due to application of data analytics

The FRC (2017), when defining data analytics, states that data analytics, when used to obtain audit evidence in a financial statement audit, is the science and art of discovering and analysing patterns, deviations and inconsistencies. It involves extracting other useful information in the underlying data or information related to the subject matter of an audit through analysis, modelling and visualisation. Ramlukan (2015: 15) defines data analytics as “the process of (and tools for) analysing data to draw meaningful conclusions.”

Data analytics is an instrument that an auditor can use to gather audit evidence through the identification and analysis of relationships between data, formulating expectations, combining data from different sources, and also using graphics or visualisations to reach conclusions (American Institute of Certified Public Accountants [AICPA], 2015; Botez, 2018). This can be done at different stages in the audit, from pre-engagement activities to planning and executing the engagement and reporting (Botez, 2018; ICAEW, 2016).

Another advantage of data analytics includes enabling quick and simple testing of the whole population by the auditor (O’Donnell, 2015) and may also help the auditor identify fraud risk indicators to develop appropriate responses to this risk (Ramlukan, 2015). The key elements of data analytics, according to Curtis, Lacome and Robertson (2020), are demonstrated in Figure 1.2.

Botez (2018) suggests that auditors still face challenges in using data analytics, despite the perception that using data analytics enhances audit quality. Some of these challenges include accessing client data to be analysed and finding knowledgeable staff to process the results of the data after it has been analysed (Mazzei et al., 2015). Despite the challenges, the auditor may use data analytics to obtain more insight into the entity’s business, enhancing the audit’s quality (Curtis et al., 2020).

Based on the preceding discussion, it is evident that despite the challenges, auditors are introducing more data analytics into their audits, as there is a growing need for auditors to enhance audit quality. However, the result of using data analytics by auditors is a topic that needs to be explored further (Maniar, n.d.; Wang & Cuthbertson, 2015). This is supported by Earley (2015), who states that even though academic research on data analytics has gained momentum, research on this topic is still lacking due to auditing and accounting firms not providing researchers with feedback on their experiences in using data analytics.

1.3         PROBLEM STATEMENT

To prevent the reoccurrence of corporate failures attributed to the quality of audits in South Africa and overcome the challenges brought by the ever-changing IT landscape, audit firms must understand what audit quality entails and the different mechanisms that can be put in place to ensure that they perform quality audits. One such mechanism is the utilisation of data analytics. Thus, the research statement is: An investigation into the role of data analytics in enhancing external audit quality in Cameroon.

The quotations below from the literature back up the research statement:

“There exists little empirical research on the effects of data analytics on the audit.” (Bender, 2017:1)

“Despite the importance of using data analytics in audit engagements to improve audit quality and the practical needs of leveraging the massive amount of available data, our understanding of using data analytics in audit engagements is still limited.” (Wang & Cuthbertson, 2015:156)

“The true extent of the use of data analytics in auditing practices is practically unknown: hence an investigation into this area is needed.” (Jacky & Sulaiman, 2022:32).

1.4         RESEARCH QUESTIONS

The following fundamental research question and its related secondary research questions are the goals of the study:

Primary research question:

• What role does data analytics play in improving the quality of external audits in Cameroon?

Secondary research questions:

• What link exists between data analytics, audit quality, and external audit?
• What is the impact of the latest technological advancements, commonly known as the Fourth Industrial Revolution, on the way firms perform audits?
• Whether audit firms in Cameroon utilise data analytics, on which engagements and during which stages of the audit process?
• What the benefits and challenges of using data analytics are?
• What effect does data analytics use has on audit regulatory inspection outcomes?