The double-edged sword of Machine Learning in South African finance

MACHINE Learning (ML) is being positioned as a game-changer in financial services, but the latest research from Experian, conducted by Forrester Consulting, suggests that the reality is more nuanced than the tech industry would have us believe.

- DIEKETSENG MALEKE

MACHINE Learning promises to revolutionise financial inclusion in South Africa, but new research reveals a complex picture of benefits and risks. This opinion piece examines whether ML is truly democratising finance or simply replacing old gatekeepers with new algorithmic ones.

While ML is making inroads across financial institutions and telcos in South Africa and abroad, its promise of inclusion, efficiency, and profitability is still entangled in practical, ethical, and regulatory complexities.

The report's headline takeaway is that ML is helping South African organisations reach thin-file and underbanked consumers, those who've historically been excluded from formal credit systems. By using alternative data sources, ML models can assess eligibility more accurately than traditional scorecards.

That sounds progressive, especially in a country where access to credit is often skewed by legacy systems and rigid criteria. But we need to ask: what kind of data is being used, and who controls it?