Abstract
The objective of the study was to analyse the Auditor General of South Africa’s (AGSA) use of data analytics to identify fraud when performing regularity audits, including AGSA’s role in identifying fraud, how they can use data analytics and how they use data analytics. The study adopted a mixed research methodology. With qualitative approach, documentary analysis was followed, which included a review of AGSA’s integrated annual reports, World Bank report and other relevant publications. The qualitative findings revealed that AGSA plays a critical role in identifying fraud during regularity audits. This is evident through the findings incorporated in the integrated annual reports. With quantitative approach, a self-administered online questionnaire survey was prepared based on the past AGSA’s annual reports and distributed to participants in order to collect their opinions on the subject of SAIs' use of data analytics. The quantitative findings were obtained through the analysis and interpretation of the questionnaire results which were organized thematically. The results from participants demonstrates that data analytics has not yet been completely incorporated into the entire AGSA’s audit process. Uncertainties on availability of relevant data, data integrity, lack of data analytics training and data overload are amongst the contributing factors highlighted by AGSA’s multi-disciplinary team of auditors. The findings further revealed that data analytics aids in maintaining high standards for financial reporting, capacity to identify fraud or rather highlight red flags which may indicate the existence of fraud, greater audit efficiency as well as time and cost savings. The findings provided concrete and indisputable evidence that technological advancements are utilised within the AGSA regularity audit process. The study provided clarity and concluded that data analytics is a helpful tool for identifying fraud or fraud related red flags. With the appearance of tremendous growth of fraud cases within the Public Sector, data analytics will play a vital role in improving identification of fraud.