While South Africa continues to make progress in terms of acknowledging the broad capabilities of artificial intelligence (AI) and the potential value that can be added across various industries and business sectors through the incorporation of machine learning, the local adoption and immersion of these technologies is still critically lagging behind global standards.
This is according to Christine van der Mescht, head of distribution at NMRQL Research, who – after attending the 71st CFA Institute’s Annual Conference in Hong Kong recently – believes that South Africa has a long road ahead in closing the AI knowledge gap that currently exists between the local and global fintech markets.
“Throughout the conference, the advancement exhibited by other countries in robotics and related fields, such as artificial intelligence, was astounding; showing an evolution from single-task devices into machines that can make their own decisions and autonomously navigate public spaces.
“Emerging economies in Asia appear to be leading this technological evolution,” she adds.
Van der Mescht refers to the world’s first fully automated, human-free bank branch in Shanghai as an example of this ground-breaking development in the field of machine learning.
“Upon entering the bank, customers of the human-free bank are greeted by Xiao Long, or ‘Little Dragon’, who is able to chat with them, accept their bank cards, and check their accounts.”
There are, however, certain barriers that do still prevent the broad use of AI in South Africa, explains Van der Mescht.
“There’s no denying that the adoption of digital technologies has been sluggish in South Africa, and in order to prevent being left behind completely, we need to acknowledge exactly what it is that has been holding the country back.
“Barriers to entry include a lack of access to local data sets, poor data quality and security, workforce readiness and re-skilling for big data insights as well as potential job losses. These barriers are enforced by a lack of trust, a reliance on old technology and an inability to shift mindset.”
With regard to investing and the management of investments, van der Mescht points out that artificial intelligence applications already exist globally that can read financial transcripts.
“This is traditionally a job reserved for human interaction – and the addition of machine learning understandably triggers fear and panic among investment professionals.”
However, van der Mescht says that throughout the conference, there was an emphasis around the idea that AI is not a replacement for human resources in asset management, but a support to them.
“It is therefore important that asset managers embrace new technology to stay relevant and enhance their productivity, rather than fear it,” she adds.
She concludes that, while South Africa still has a number of challenges to overcome before effectively closing this knowledge gap, there is no denying that AI will play an increasingly important role in the investment space, driven largely by machine learning techniques.
“Whether we like it or not, the global investment space has embraced the use of machine learning to support its investment decisions – it is about time that the South African market does the same and views this technology for the positive, supportive contributions it can make toward growing our asset management space to compete on a global scale.”