Artificial intelligence is reshaping the financial services landscape at a pace that few could have predicted even five years ago. From automated credit scoring to AI-driven fraud detection, the technology is delivering measurable efficiency gains — but it also introduces new categories of risk that financial professionals and their advisors must understand.
Where AI Is Making an Impact
Bookkeeping and Reconciliation: AI-powered tools can now categorise transactions, flag anomalies, and complete bank reconciliations with minimal human intervention. For accounting firms and their clients, this translates to faster month-end close processes and reduced risk of manual error.
Tax Compliance: Machine learning models are being used to identify tax optimisation opportunities and to flag potential compliance issues before they become problems. SARS is also investing in AI-driven audit selection, meaning that businesses with inconsistent or anomalous financial data are increasingly likely to attract scrutiny.
Fraud Prevention: Financial institutions are using AI to monitor transaction patterns in real time, identifying suspicious activity far more quickly than traditional rule-based systems.
The Risks That Come With AI
Speed and scale bring their own challenges. AI systems can entrench existing biases if trained on unrepresentative data, and the "black box" nature of some models makes it difficult to explain decisions to regulators or clients.
There is also the question of data governance. AI tools require access to large volumes of financial data — and businesses must ensure that their use of this data complies with the Protection of Personal Information Act (POPIA) and other applicable legislation.
Our Perspective
We believe AI is a powerful tool for enhancing financial service delivery, but it works best when combined with experienced human judgement. At J Rawat and Company Inc, we stay current with technology developments to ensure our clients benefit from innovation without being exposed to unnecessary risk.