Artificial intelligence technology to enhance data quality management practices in the banking industry in South Africa

Abstract

Data generated and used for decision-making in the banking sector has enabled the industry to overcome different challenges and gain insights to improve customer satisfaction. The importance of high-quality data in the banking industry is imperative to reduce fraud and financial crimes, and to enhance financial decision-making. It is therefore important that good data quality management practices are adopted to secure the stability of financial organisations. The purpose of the research as a concept paper was to propose a conceptual framework for utilising artificial intelligence (AI) technology for data quality management. This study explored the components of a proposed conceptual framework for the utilisation of AI technology for data quality management in the banking sector. In applying a qualitative desktop review, the hourglass model for AI governance and the Data Management Association (DAMA) model was used to develop a proposed conceptual framework relevant to the banking industry. Themes included in the proposed conceptual framework related to legislation and regulations, principles and guidelines, people, strategy, and technology/systems. The literature review’s results showed that in South Africa, limited legislation and guidelines are available to support and advance the use of AI in data quality management. It is envisaged that the proposed conceptual framework will provide a reference point to further explore this topic.