Use of data analysis techniques by small and medium-sized audit practices

Abstract

Organisations are facing growth in the digitisation of their processes, causing rapid growth in the creation of electronic data. Electronic data arise from different sectors of business processes such as operational, financial and others. The introduction of the Industrial Age has accelerated the Information Age. This rapid growth has brought the world to the Fourth Industrial Revolution. Internal auditors are expected by their professional body to fulfill the mandate of adding value to organisations by reducing risks that threaten the achievement of their goals. This calls for better techniques that are modern. The purpose of the study was to investigate the factors that contribute to the successes and failures in other areas of audit by small and medium-sized audit practices. This was necessary because the Global Institute of Internal Auditors (IIA) regards an effective internal audit organisation as that which applies data analysis, data extraction and analytical software tools. The study was conducted using a qualitative research approach. This study adopted two theoretical frameworks, which is fuzzy set theory and grounded theory. The fuzzy set theory works best when there are no or few researchers in that field of study. Indeed, this study has random elements of fuzzy set variables, which are vague and imprecise information. In addition, it was necessary to use grounded theory because of the intention to reveal insights. Data was collected through unstructured questionnaires conducted with 10 internal auditors. Data was analysed through themes using NVivo. The empirical findings indicated that the transformation of the internal audit activity by small and medium-sized internal audit practices require much more data analytical development than the technical capabilities to be at the most matured state of using data analytics.