Smart, transparent, and scalable decisioning architecture is becoming business-critical for South Africa’s banks, telcos, and insurers, writes Nikhil Behl, president: software at FICO.
South African enterprises are under mounting pressure to do more with their data ethically and at scale. As customer demands intensify and regulatory scrutiny grows, the systems that sit behind critical business decisions are coming into the spotlight. AI decisioning platforms, once considered a nice-to-have, are fast becoming essential infrastructure for organisations that want to compete in the next era of digital transformation.
More than three-quarters of enterprises are using AI in at least one business function, says McKinsey, with an estimated long-term value of an estimated $4.4 trillion. The technology is reimaging decision-making, tasks and complex workflows, and companies, as the research firm so eloquently puts it, are rewiring for the value it offers.
Ongoing investment and adoption are a strong signal that the market is heading towards a level of maturity that demands more from these platforms. Transparency, modularity and governance have become critical, especially for the South African business.
This comes at a time when the pressure on local institutions to operationalise AI at scale is intensifying. Banks, telcos, insurers, and retailers are managing increasingly complex customer journeys and risk profiles while navigating compliance obligations under legislation like POPIA and Treating Customers Fairly. Many are still contending with legacy infrastructure, siloed data environments, and rigid decision frameworks that are struggling to adapt to modern business demands.
At the same time, consumer behaviour is evolving. Financial institutions are under pressure to strike a delicate balance between extending credit access and managing risk exposure. A challenge made harder by outdated decision engines that lack real-time responsiveness or explainability.
AI decisioning platforms have emerged as strategic assets as they support faster approvals and real-time risk checks while also bringing structure to complexity. They enable institutions to codify policy, simulate business outcomes, test risk strategies, and automate interventions with clarity and control. In markets like South Africa, where the cost of error is high and consumer protection is closely watched, the ability to audit and explain decision logic is important, and highly relevant.
Regulatory scrutiny in South Africa is intense and the ability to audit and explain logic is critical for both lenders and consumers. Modern AI decisioning platforms are increasingly adopted precisely because they offer end-to-end audit trails, versioned decision logic, and explainable AI functions. They provide the ability to justify a decision to both the customer and the regulator.
With the Protection of Personal Information Act (POPIA) in full enforcement and digital fairness increasingly under scrutiny, institutions must ensure that decisions are not just accurate, but defensible. These features allow organisations to track every decision back to its origin, reproduce outcomes when challenged, and present evidence of compliance in audits or disputes.
These platforms help organisations think beyond traditional rule-based models and move towards a state where AI agents can adapt autonomously to changes in data or policy while keeping humans firmly in the loop.
For many South African institutions, this capability is the foundation for everything from pre-emptive fraud detection to credit repricing, churn prevention and dynamic loan structuring. It’s also critical for embedded finance strategies, where decisions must happen instantly at the edge of digital ecosystems, often with limited customer history and under strict governance expectations.
AI decisioning offers a scalable solution. These platforms allow institutions to manage increasingly complex customer lifecycles and data environments, automating decisions such as:
- Determining creditworthiness in real time
- Dynamically adjusting pricing or limits
- Detecting and stopping fraud mid-transaction
- Managing regulatory rules with full audit trails
While there’s growing buzz around generative AI, it’s important to understand that these kinds of platforms are not about GenAI alone. They are about using a combination of AI, advanced analytics, business rules, and other integrated capabilities to drive accurate, consistent, and context-aware decisions at enterprise scale. This is about operationalising intelligence—not just generating content but embedding smart decision-making into the core of how the business runs.
AI decisioning is now foundational to South Africa’s digital financial infrastructure. Institutions that move decisively to embed transparent, scalable and auditable decision platforms will be best positioned to handle complexity, meet compliance demands and deliver real-time value to customers. The time for cautious experimentation is over. What’s needed now is full execution because it is about to become a competitive advantage.