The Role of AI in South Africa’s Financial Sector

The Financial Sector Conduct Authority (FSCA) and the Prudential Authority (PA) have jointly published their inaugural report, Artificial Intelligence in the South African Financial Sector. This report provides the first comprehensive overview of AI adoption, including machine learning (ML) and generative AI (GenAI), within South Africa’s financial institutions.

Informed by a survey of banks, insurers and investment managers that was conducted in 2024, as well
as global developments, the report reveals a steady increase in AI usage. Banks are at the forefront, with 52% of banking institutions actively employing AI, followed by payment providers1 at 50%. Investment intentions vary across the sector: while most institutions plan modest investments under R1 million, more than half of bank respondents anticipated investing over R20 million in AI technologies during 2024.

The report highlights key opportunities to improve data analytics, operational efficiency and cybersecurity measures. However, it also identifies significant risks, including consumer risks such as data privacy concerns, bias and discrimination, reputational risks and systemic vulnerabilities. Constraints to broader adoption include regulatory uncertainty, shortages of skilled professionals and difficulties with explainability and governance.

Emphasising the need for ethical and responsible AI deployment, the report considers the need for robust governance frameworks, improved transparency and stronger consumer protection measures. Lessons learned include prioritising high-impact use cases, developing clearer disclosure requirements and promoting digital and AI literacy across the sector.

Lessons learnt

As AI technologies continue to evolve, their integration into South Africa’s financial sector will require a coordinated and forward-looking approach. The FSCA and PA have identified several key learnings from the data analysis:

• Explainability and transparency: Institutions are encouraged to adopt recognised explainability methods ‒ such as SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) ‒ to ensure AI-driven decisions are more understandable and auditable.
• Governance frameworks: Financial institutions should consider comprehensive governance structures, including strong data governance, model risk management and board-level oversight, to ensure ethical and effective AI deployment.
• Regulatory coordination: The FSCA and PA would like to collaborate closely with the Information Regulator to ensure alignment with the Protection of Personal Information Act 4 of 2013 (POPIA), particularly in relation to data privacy and consumer protection.
• Prioritisation of use cases: To ensure that the benefits of AI are maximised, it is key for certain use cases to be prioritised so that their associated risks can be effectively managed.
• Ethical standards and oversight: The development of sector-wide guidance for ethical, fair and responsible AI is envisaged, alongside enhanced oversight to mitigate bias, inaccuracies and consumer harm.
• Efficient and effective disclosure: Institutions should clearly disclose when AI is used in consumer-impacting decisions, such as credit assessments or insurance pricing.
• Digital and AI literacy: Promoting consumer education and awareness will be critical to ensure that individuals understand how AI affects their financial decisions and rights.

These insights reflect a shift towards a more inclusive, transparent and resilient financial system that leverages AI responsibly to benefit both institutions and consumers.