The instrumentation of detective analytics for mitigating financial crimes in South African institutions

Abstract

The occurrence of financial crimes in South Africa has been significantly high. This is because many financial institutions conduct their operations through online, digital platforms. Digital operations in financial institutions increasingly rely on digital platforms due to the high demand for real-time quick services. This results in generating unprecedented data. Organisations use the data to make informed decisions, which increases the significance. The reliance on data has made financial institutions adopt and use tools such as detective analytics. However, the implementation of detective analytics remains challenging to individuals and organisations at large. The challenges are attributed to a lack of understanding of the factors that influence the implementation of detective analytics. There are concerns that the current data analytics tools being used by financial institutions have gaps and loopholes. Consequently, financial crimes are often identified only after their occurrence. This study aimed to develop a tool that can be used to implement detective analytics to mitigate financial crimes. In achieving this aim, the researcher followed the case study approach using a South African financial institution as a case. The organisation was selected with a set of criteria. Qualitative research methods involving interpretive and semi-structured interview techniques were used to gain an in-depth understanding of the factors influencing financial crimes in South African financial institutions. The study employed the subjective approach from the interpretive perspective to gain insights into how detective analytics can be applied to mitigate financial crimes in financial institutions. Semi-structured interviews were conducted with business and information technology (IT) specialists. Also, the participants were selected using a set of criteria. The interviews stopped at a point of saturation, which means that no new information was forthcoming. Additionally, existing documents were gathered and used to complement the interview data. The university (CPUT) and the organisation’s ethics, including participants’ consent, guided the data collection. The data was analysed using the four moments of translation actor-network theory (ANT as a lens to guide the data analysis. The theory was selected primarily for three reasons. Firstly, it focuses on translation, required to understand how meanings are associated with events and processes in mitigating financial crimes. Secondly, ANT enables an understanding of how actor networks are consciously formed, which helps to determine the formation of groups responsible for mitigating financial crimes in the organisation. Thirdly, ANT’s mantra “follow the actors” was employed to follow the actors, from humans to non-humans, helping to gain a deeper understanding of why things happened in the ways they did in mitigating financial crimes in the organisation. From the analysis, seven factors were found to influence the use of detective analytics to mitigate financial crimes in organisations. The factors are as follows; (1) Collaboration; (2) Corroboration; (3) Internalisation; (4) Externalisation; (5) Digitalisation; (6) Organisational structure; and (7) Integrated analytics. Activity theory (AT) was used as a lens to guide the interpretation of findings. The interpretation revealed the links between the influencing factors (findings) including their attributes. Based on the influencing factors, the links, and the attributes, a framework was developed, which can be used to guide the adoption and implementation of detective analytics to trace, track, and prevent financial crimes in financial institutions in South Africa. The study contributes to both business and academic domains from theoretical, practical, and methodological perspectives. Theoretically, the relationships between the influencing factors are established. Practically, organisations can develop policy and governance frameworks to prevent financial crimes, based on the influencing factors. Methodologically, the application of ANT and AT advances the use of sociotechnical theories in detective analytics.