Adoption of Artificial Intelligence within the Financial Services Sector in South Africa

Abstract

Artificial Intelligence (AI) I involves the development of computer software systems that simulate human intelligence. Institutional adoption of AI technology has grown exponentially due to its disruptive potential towards traditional financial sector processes. AI applications have played a positive role in the financial services sector processes by reducing operating costs, improving process efficiency, and managing operating risks these institutions face globally. While these benefits can potentially solve societal problems, such as an unproductive workforce, AI applications could increase social inequalities by using non-representative or biased data in their design. The research study explored the adoption of AI within the financial services sector, with a particular focus on its perceptions, benefits and challenges. Data was collected using a systematic literature review by analysing the relevant academic articles, industry and regulatory reports on AI adoption in South Africa. In addition, semi-structured interviews with four professionals within the financial services sector of South Africa through purposive sampling. The research study found that the perceptions of AI in the South African financial services sector are negative, which is attributed to the impact of AI towards the job market within this sector. The benefits of AI are mostly observed from the risk management perspectives, customer experience and productivity, which are the major influences on the intention of financial services firms to adopt AI. The challenges found in AI adoption within the financial services sector relate to the lack of AI skills, age and regulatory issues. Lastly, financial services firms that disseminate information about the benefits, use cases and practical implications of AI within their internal operating environment were seen to be drivers of AI adoption. Financial institutions adopting AI should focus on investing employee skills, data management practices and Explainable AI (XAI) to improve efforts towards greater AI adoption in the sector.