At the event, which brought together senior technology and business leaders from across the banking, financial services and insurance (BFSI) sector, James MacDonald, Senior Customer Success Manager at SAS South Africa, spoke on the theme Transforming banking and insurance with predictive insights and hyper-personalised solutions.

The discussion came at a time when the sector is navigating a perfect economic storm: rising cost-of-living pressures, household cash-flow stress, regulatory expansion, and new risks linked to climate, fraud, conduct, and geopolitical volatility. At the same time, customer expectations are shifting faster than most institutions can update their systems. Fintech competition, GenAI, real-time channels, and API-driven architectures are forcing banks and insurers to rethink how decisions are made across the enterprise.

As MacDonald noted, the industry is moving away from siloed technologies and toward a single architecture with a single decision engine. This model delivers consistent, explainable decisions across marketing, risk, fraud and service, and helps BFSI leaders run the bank of today while building the bank of tomorrow. 

MacDonald explained that many financial institutions still treat decisions as separate projects in marketing, risk, fraud, and operations. The result is a patchwork of models, rules, and campaigns that compete for the same customer rather than working together. 

“Customers experience the whole organisation, not individual systems,” said MacDonald. “If banks and insurers want to be relevant and trusted, they need a single decisioning brain that understands context, weighs risk and value, and chooses the next best action in real time, regardless of the channel.” 

From campaigns to enterprise decisioning 

Drawing on SAS’s work with global and regional institutions, MacDonald outlined how an integrated approach to enterprise customer decisioning helps BFSI organisations future-proof their businesses. Instead of building one model per campaign or product, institutions centralise decision-making logic in a platform that can weigh multiple signals simultaneously, such as customer behaviour, credit risk, fraud indicators, and service history. 

This approach supports a shift from channel-centric thinking to customer-centric outcomes. It allows a bank or insurer to ask, in every interaction, “What is the best decision for this customer right now, given our risk appetite, regulatory obligations and long-term relationship?” 

According to MacDonald, the benefits are not only commercial. A consistent decisioning layer helps institutions demonstrate fairness, traceability, and regulatory compliance by enabling them to show how each decision was made, which data were used, and which policies were applied. 

Predictive insights and hyper-personalised journeys 

MacDonald highlighted how predictive analytics and machine learning models inside the decisioning platform can identify intent and risk earlier in the customer journey. For example, propensity models may flag which customers are most likely to respond to a retention offer, while risk models highlight which applicants require additional checks before approval. 

“Hyper-personalisation is not about showing different banners on a web page. It is about aligning every decision across marketing, risk, fraud, and service so that customers feel recognised and treated fairly, whether they are opening an account, filing a claim or restructuring debt.” 

SAS technology enables BFSI organisations to orchestrate these decisions across channels, including mobile apps, contact centres, the web, branches, and partner touchpoints. This helps eliminate conflicting messages, such as a collections call arriving after a renewal offer, or a high-risk transaction being approved in one channel while blocked in another. 

Real-time decisions at scale 

A key theme in MacDonald’s session was the importance of real-time decisioning. Customers expect instant responses, whether they are applying for a loan, requesting a quote or disputing a transaction. Batch-based processes cannot meet these expectations. 

“In modern BFSI, real-time has become the baseline. Enterprise customer decisioning gives banks and insurers the ability to evaluate context and risk within milliseconds, then trigger the right action, whether that is an approval, a step-up authentication, a fraud alert, or a tailored offer,” he said. 

MacDonald pointed to industry use-cases where integrated decisioning can help financial institutions increase cross-sell effectiveness, reduce churn, and improve loss ratios in insurance, while also cutting operational costs through smarter automation. 

Preparing for the next wave of disruption 

The BFSI Summit session also looked ahead to the impact of artificial intelligence (AI), including generative AI on customer decisioning. MacDonald cautioned that new capabilities do not remove the need for governance. Instead, they emphasise transparency, model management, and ethical guidelines. 

“As AI becomes more embedded in front-office and back-office decisions, the institutions that will thrive are those that treat governance as part of the design, not an afterthought. Enterprise decisioning gives them a foundation where every model and rule is visible, explainable and governed across the organisation.” 

He added that SAS is working with banks and insurers in South Africa and across the region to modernise legacy decision flows, connect siloed systems and prepare for new regulatory expectations on fairness, explainability and resilience. 

“SAS’s role is to bring proven platforms, domain expertise and an integrated view of the customer so that BFSI leaders can act with confidence. Events like the BFSI Summit show that the appetite for change is real. The next step is turning that appetite into decisions that customers feel in every interaction,” concluded MacDonald.